Lecture Series in Mobile Telecommunications and Networks (1583KB)

Lecture Series in Mobile 

Telecommunications and 

Networks 

Transcripts of the third series of three lectures 

March 2008 - February 2009

Lecture Series in Mobile 

Telecommunications and 

Networks 

Transcripts of the third series of three lectures 

March 2008 - February 2009 

© The Royal Academy of Engineering 

ISBN: 1-903496-42-X 

April 2009 

Published by 

The Royal Academy of Engineering 

3 Carlton House Terrace 

London 

SW1Y 5DG 

Tel: 020 7766 0600 Fax: 020 7930 1549 

www.raeng.org.uk 

Registered Charity Number: 293074

Foreword 

This compilation brings together the transcripts of the third of a series of lectures on the 

subject of Mobile Telecommunications and Networks. The lecture series was established by 

The Royal Academy of Engineering and Vodafone to celebrate the enormous social and 

economic benefits that mobile communications have given us – a success story brought 

about and maintained by excellence in communications engineering. The three lectures in 

this series were given over the period between March 2008 and February 2009. All three 

were exceptionally well attended and generated enthusiastic and lively debate and 

discussions. 

The series was opened by Professor P R Kumar, Franklin W Woeltge, Professor of Electrical and 

Computer Engineering, at the University of Illinois. His lecture addressed the converging 

worlds of communications, computation and control – described through infrastructure - 

free wireless networks, and illustrated with fascinating films of model systems created at the 

University of Illinois. 

The bedrock of all wireless communications systems is radio frequency spectrum, and this was the subject of the 

second lecture, given by Professor Linda Doyle of the Department of Electronic and Electrical Engineering at the 

University of Dublin. She entered into the debate of how one should allocate and manage spectrum, covering 

approaches from classical ‘command and control’ to dynamic ‘grab what you need when you need it’. Her lecture gave 

rise to the most lively debate we have had during the Questions and Answers sessions. 

Most lectures on mobile communications nowadays are concerned with subjects like broadband access, convergence, 

mobile widgets or the phone as a computing device, so it was refreshing that in the final lecture of the series Professor 

Peter Vary of the University of Aachen returned to basics – voice communications. In a fascinating lecture he covered 

the history of and contemporary research on speech coding for mobile communications, providing great insight into 

what is the most important function of the phone. 

Professor Michael Walker FREng 

Research and Development Director 

Vodafone Group 

2 The Royal Academy of Engineering

Contents 

From wireless networks to sensor networks and onward 4 

to networked embedded contrtol 

Professor PR Kumar 

Questions & Answers 18 

To the edge of chaos? 

The complexity and the promise of a technology and service-neutral future 21 

Professor Linda Doyle 


From plain old Telephony to flawless mobile audio communication 44 

Prof Dr Ing Peter Vary 


The Royal Academy of Engineering 3

From wireless networks to 

sensor networks and onward to 

networked embedded contrtol 

Wednesday, 26 March 2008 

Speaker: 


Franklin W. Woeltge Professor of Electrical and Computer Engineering, 

University of Illinois 

Chair: 

Professor Mike Walker FREng 

Research and Development Director, Vodafone Group 


Welcome and introduction 

Professor Michael Walker (Chair): Good evening, ladies and gentlemen. For those of you who do not know me, I am 

the Research and Development Director for the Vodafone Group, and I would like to welcome you here this evening to 

the first lecture in the third series of lectures in mobile telecommunications and networks. These lectures are hosted by 

The Royal Academy of Engineering and sponsored by Vodafone. 

For those of you who are attending these lectures for the first time, let me just say a little about their purpose and 

history. To put things in perspective, at the moment more than 3 billion people in the world carry a mobile phone: 

more than half the population of the planet now have a mobile phone. Eighty per cent of those phones use one 

technology, GSM, which was invented in Europe and the UK played a very significant role not just in the invention of 

that technology but also in its commercialisation. This is a huge achievement. 

It has transformed people’s lives. I do not know any business that does not now rely on its employees having mobile 

phones for all sorts of things. Pretty well everybody in the Western world who wants a mobile phone has one – if 

people do not have one, it is because they choose not to and not for any other reason. Perhaps more importantly, in 

many developing countries, the mobile phone has been a force for total social change. Rural populations, for instance, 

can keep in contact with each other and the markets in which they sell their products. A few years ago, Kenyan farmers 

or Kenyan fishermen had no idea of the price of their product on the market: now, they know the price of their product 

on the market before they start harvesting, and that is all down to mobile phones and what you can do with them. 

This is a tremendous development in something under 20 years. 

The purpose of these lectures, when we instigated them three years ago, was to celebrate the tremendous engineering 

innovation that is still behind mobile systems and still contributing to their development today. 

Before we start the third series, I should just mention that the second series is available in a brochure which contains 

each lecture. Each series consists of three lectures, the first of which is always hosted here at the Royal Society, with the 

subsequent two taking place within the Royal Academy itself. For the first lecture, we always invite a world famous 

figure in the subject of mobile communications and its applications and tonight it is my pleasure to introduce Professor 

Kumar. Before I invite him to take the lectern and deliver his lecture, let me say a few words about his distinguished 

career. I hope you will forgive me if I keep referring to my notes here, because his career has been exceptionally long 

and distinguished and I could not possibly remember everything. 

Professor Kumar started with his first degree in Electrical Engineering at the IIT Madras in India. He then went to the US 

and read both Systems Science and Mathematics at Washington University, St Louis. He became a member of the 

Department of Mathematics at the University of Maryland and then, since 1985, he has been at the University of Illinois 

in Urbana, where currently he is the Franklin W Woeltge Professor of Electrical and Computer Engineering. 

Professor Kumar has received the Donald P. Eckman Award of the American Automatic Control Council; the IEEE Field 

Award in control Systems, and the Fred Ellersick Prize of the IEEE Communications Society, which was awarded in 2007. 

He is a fellow of the IEEE and a member of the US National Academy of Engineering. 

He has worked on problems in a huge number including game theory; adaptive control; stochastic systems; simulated 

annealing; neural networks; machine learning; queuing networks; manufacturing systems; scheduling and wafer 

fabrication. The list goes on to sensor networks and the subject about which he will talk tonight. 

The title of Professor Kumar’s lecture this evening is From Wireless Networks to Sensor Networks and Onward to 

Networked Embedded Control. Professor Kumar, I invite you to take the podium and address us. 


From wireless networks to sensor networks and 

onward to networked embedded contrtol 


Franklin W. Woeltge, Professor of Electrical and Computer Engineering, University of Illinois 

Thank you, Professor Walker, for that kind introduction. I must say that it is a great honour to be present in such an 

illustrious place in front of such a distinguished audience. Thank you for inviting me. 

I shall be talking about three things: wireless networks, sensor networks and network embedded control. 

The oncoming wireless era: from communication to sensing control 

6 The Royal Academy of Engineering 

The underlying key is that we may be on the cusp of a 

wireless era. Let me sketch the elements of what that era 

could be. As Professor Walker pointed out, we are very 

much in the cellular systems era and countries like India 

and China are adding 8 million or so phones per month. 

I will look a little into the future, to see what else may be 

coming down the road. 

I will be talking about wireless networks where there is no 

need for any infrastructure. In cellular systems, there is a 

wired infrastructure and your telephone makes one wireless 

hop to the infrastructure and then it travels with the wired 

network. In the future, however, we may all be talking to 

each other without any infrastructure. 

It is not just communications. Already, we have these small gadgets. This is what is called a moat and it comes out of 

the University of California, Berkeley. You can connect your favourite sensor to that – it could be temperature sensor, or 

a light sensor, or a magnetic sensor or whatever. That gives you the ability to sense the environment, in addition to 

communication and computing – but it does not stop there. None of us is content with sensing and, the moment we 

sense something, we want to take action. I am not content with just knowing the speed of my car, but I want to go 

faster or slower. Once we have sensing and acting, that is called control and we may be exercising control 

over networks. 

In the US, since last year people have been talking about a new phrase, ‘cyberphysical systems’, and these are computers 

interacting with the environment, the cyber and the physical worlds coming together. This is really the convergence of 

communication, computation and control, and that is what I want to talk about. 

Ad hoc wireless networks 

There are several themes, the first of which is wireless networks. The type of wireless networks I shall be talking about 

are what are called ‘ad hoc wireless networks’. These are things that you can set up spontaneously, anywhere. A bunch 

of us could open up our laptops in this room or on a campus and then we could start interacting with each other. 

The current proposal for operating such wireless networks is what is called multi-hop relaying. How does that work? 

Let us say that this node wants to send packets of information to that node. This thing here says, ‘I want to talk’, and the 

nodes which hear it agree to keep quiet. Then this node says, ‘Okay, go ahead and talk to me’, and any node which 

hears that also keeps quiet. At this point, the neighbours of both these nodes have kept quiet and that facilitates a 

packet from here being sent to there, and being received without nearby interference. We can also send an 

acknowledgement back, saying ‘I received your packet’. So this four-phase handshake takes place and the packet of 

information makes one hop. It then continues on in a similar fashion until it reaches its destination, and that is a multihop 

wireless network.

From wireless networks to sensor networks and onward to networked embedded contrtol 

Application Layer 

Transport Layer 

Network Layer 

MAC 

Physical Layer 

Interference 

+ 

Interference 

+ 



Network Layer 

MAC 

Physical Layer 

Interference 

+ 

Noise Noise 

Noise 

Signal Signal Signal 

All of these operations can be mapped onto an architecture, 

which is reminiscent of an OSI stack. If you look a little 

more closely at this, what is really happening is that this 

node sends a packet, which is basically a radio signal, to 

that node. However, that is not the only thing that this 

receiver is hearing because there is also concurrent 

interference and noise. The thing about the wireless world 

is that it is a shared medium and so, if two people are 

talking to you simultaneously, perhaps you cannot 

understand either one of them. That is why there is this 

four-phase handshake, which attempts to keep your 

neighbours quiet, so that you reduce the interference. 

Then, the signal is decoded in the presence of interference 

and noise – interference from different faraway sources, and digitally regenerated, so that you are buying into the digital 

evolution at this point, and then re-transmitted, regenerated and transmitted to the next node which, again, decodes it 

in the presence of interference plus noise, forwards it to the next node, and so on. 

The point is that wireless transmissions interfere with each other, so there is a great deal of handshaking and so on to 

mitigate the interference. In fact, that is what lies behind the notion of spatial re-use of frequency. In the cellular world, 

for example, supposing you use your blue frequency in your local cell, then it is not used in an adjoining cell but it may 

be used further away. So frequency is re-used at a different point in space, further away from where this conversation is 

going on. 

One question you could ask is, how much traffic can wireless networks carry when we treat interference as noise? Is it 

possible that the entire world can become wireless and that we can just get rid of all wires altogether? 

Scaling law for wireless networks 

We really want to study the scalability of wireless networks 

and how large they can get. This slide shows a model and 

let us suppose that I have some domain and, in that 

domain, let us suppose that there are n nodes, randomly 

located. You never know where your users will be, so 

suppose that they are randomly located in this domain. 

Let us suppose that every node wants to talk to some other 

random destination and that it wants to send traffic at the 

rate of lambda bits per second throughput, to the 

destination. Similarly, all the other nodes also want to send 

lambda bits per second. 

The question you can then ask is, what is the largest lambda 

you can support? What is the largest throughput that you 

can furnish to each user in a large wireless network with n nodes? Here is the result. It says that the probability that you 

can support a multiple of [1 over square root n log n], converges to 1 as n goes to infinity. There is a larger multiple, 

whose probability of being supported can resist to zero. This is what is called a sharp cut-off phenomenon and it tells 

you that a wireless network essentially can support [1 over square root of n log ] in bits per second per user. This means 

that there is a law of diminishing returns: as the number of users increases, what you can provide to each user decreases 

and so we cannot get rid of wires with this technology. As you try to accommodate more and more people, each of us 

will have to give up some of our own throughput. 

We also understand architecture when we treat interference as noise. Here is an order optimal architecture, so here are 

your random nodes. It turns out that you can operate it in a cellular fashion, which means that you can divide up 

groups of nodes into cells, very much like the cellular systems. All nodes choose a power level which is sufficient to 

reach nodes in neighbouring cells. Basically, you can have nearest neighbour conversations. 


As far as the routing of packets is concerned, it turns out that you can pretty much follow a straight line path, and such 

straight line paths will average out the load over the network so that there are no hotspots. That is an order optimal 

architecture. That is what we will get if we treat interference as noise and there is a law of diminishing returns, as I have 

pointed out. 

But is spatial reuse the right design principle? 

better than deserts for wireless networks, if that is true. 

However, the fundamental question to ask is, is spatial reuse 

the right design principle? Why do I want to challenge 

that? As I pointed out, spatial reuse, as we can see, is not 

used in an enabling cell but further away. If you really 

believe in spatial reuse of frequency, then you should 

believe that a sharper path loss is better for wireless 

networks. What do I mean? As radio signals travel, their 

amplitude attenuates. This is a gradual attenuation [on 

slide] and that is a more rapid attenuation. The philosophy 

behind spatial reuse is that if you do not want to have 

interference from people further away then you should 

prefer a sharper attenuation. If you believe in that, then you 

should believe that this [on slide] is better than that. Or, to 

put it more colourfully, you should believe that jungles are 

Is spatial reuse really the right way to operate wireless networks? 


The problem is that wireless networks are formed by nodes 

with radius, not with wires. Therefore, to draw a picture like 

this is wrong, and it is reminiscent of wires. Actually, you 

cannot see it here, but we have a whole bunch of antennae 

which are just radiating energy. That is the picture of a 

network that you should have, with everybody talking away. 

There is no a priori notion of links – nodes simply radiate 

energy and so the network is Maxwellian rather than 

Kirchoff. In the Maxwellian world, strange things can 

happen. Nodes can actually co-operate in much more 

complicated ways than they could in a wire-line network. 

For example, it turns out that if somebody shouts in your 

ear at the same time as somebody else is whispering softly, 

Shannon would actually say that was fantastic. In fact, the 

louder this person shouts, the better. Why? Because, when this person shouts really loudly, you can decode that person 

perfectly and subtract out that person’s signal if you know the channel activation, and pick up the whisper. It turns out 

that it is actually more difficult and you can decode neither of them – so that when one is louder, that is actually better 

for you. The point is that interference is not interference: everything is information – even interference – and the only 

question is how you deal with it. 

Here is another bizarre notion. We have this notion of signal to interference plus noise ratio. Signal is the good guy and 

interference and noise are the bad guys, and this ratio tells you how good the signal is, compared to what is interfering. 

Usually, we try to mitigate interference but perhaps we can try to cancel interference actively, just as in your acoustic 

sound-cancelling headphones. For example, this node could transmit something which cancels the effect of what this 

node is transmitting at this point, so you can have co-operative cancellation and perhaps you should try to reduce the 

denominator. 

Alternatively, perhaps you should not even buy into the digital revolution. Instead of re-generating the packet at each 

intermediate node, why not just amplify what you heard, without bothering to decode? In fact, the information is only 

intended for the final destination, so why should you insist that intermediate nodes should be able to decode


information? In fact, if you are sending this information over multiple paths to your destination, then perhaps it is only 

the case that the end-point has sufficient signal strength to decode the information, and not the intermediate points. 

Thus, this architecture of decoding and treating interference as noise limits itself from the start. As Shakespeare said, 

through Hamlet, the world is extremely complicated. The fundamental question is, what is the best architecture for 

wireless networks? The point is that the design space is infinite-dimensional and there are so many sophisticated things 

we could do. To get to the bottom of this, we have to seek answers with information theory. 

Network information theory 

As many of you know, information theory was invented by 

Claude Shannon in 1948, about 60 years ago. A very 

celebrated formula, for example, is the capacity for Gaussian 

channel which says that, if you have a spectrum of 

bandwidth (B), signal strength (S) and noise strength (N), 

then this is the absolute limit on the number of bits per 

second of information that you can transmit. So, for 

example, if you have a telephone wire and you tell me how 

much noise there is on it, Shannon tells us exactly how 

much throughput that wire can take. That kind of 

fundamental result allows for any mode of operation: no 

matter what you do, you cannot beat this formula. This is 

fundamentally good because, once you have some kind of 

law of thermodynamics, you have some limit, then you 

know when you are close to it that you can quit trying. 

Information theory has had much success in point-to-point communication: point-to-point means one person talking 

to another. However, we are in the world of networks and not just one transmitter and one receiver, but we have a 

whole bunch of people co-operating to transmit information to each other. So how should we do it? 

Here is the result, which is a theoretical one which says the following, under some assumptions. It says that if your path 

loss is sufficient, then multi-hopping is indeed the order of real architecture. That is the way that the present design 

efforts have been going, and that is indeed the right choice. So, out of this whole complicated space, what we have 

been doing is the right thing but, unfortunately, it also means that there is a law of diminishing returns. We cannot beat 

this limit, even if you throw over the digital revolution and even if you decide to have these other strategies. 

In-network information processing 

Let me move on to another theme: in-network information 

processing. I am now talking about what are called ‘sensor 

networks’. Instead of just having the facility to 

communicate and perhaps to local computations on your 

processor, nodes can also sense their environment, so you 

can plug in your favourite sensor there. 

What tasks might be a sensor network be deployed to 

perform? There is environmental monitoring and so, for 

example, in some domain you may throw a whole bunch of 

nodes, all of which measure the temperature. Being 

extremely simplistic, let us suppose that the n nodes which 

take the temperature X1 to XM, and that perhaps there is 

some collector node or a sink – then what the sink is 

interested in is the average temperature of the domain. You just want to monitor the average temperature. 

Or, perhaps on an alarm network, perhaps a collector node may be interested in the maximum temperature. Is there a 

fire, or isn’t there? The point is that sensor networks are not just data networks. You should not think of sensor networks 

as just good old communication networks where you simply replace files by sensor measurements, for the following 


easons. In the internet, one never looks inside another person’s packet. For example, I do not look at your packet and 

say, ‘This is not interesting information – I will drop it.’ However, in a sensor network I may do that. If I see a high 

temperature, then I may drop a low temperature. So, depending on what I have heard, I may say that this information is 

uninteresting, or I confuse information and combine information and so on. The point is that in sensor networks, the 

nodes do not just forward information but they also compute. In other words, they process information in the network 

– the network itself processes information, and so this whole thing is like a Maxwellian computer, if you will. 

There are many interesting questions that you can ask and I will say something really simplistic. Let us say that I want to 

compute a symmetric function in a sensor network. What is a symmetric function? It is one where, if you change the 

identity of which node has which temperature, the result does not change. For example, the average is invariant to 

permutations. In fact, most statistical quantities are symmetric functions. 

Computing symmetric functions: the mean versus max 

Theorem: The rate at which the Mean can 

be harvested is 

– Strategy 

Tessellate 

Add locally 

Sum along a rooted tree of cells 

Theorem: The rate at which the Max can be 

harvested is 

Strategy: Take advantage of Block Coding 

– First node announces times of max values: ( 1 1 1 ) 

– Second node announces times of additional max values (1 ) 

1 

– third node announces of yet more max values: ( ) 

1 

(Giridhar & K03) 12/34 

It turns out that we are very much at the beginning point of 

developing theories for how to operate such networks. 

What I would like to illustrate for you is a kind of dichotomy 

about how you treat different functions. It turns out that 

the rate at which you can exfiltrate average temperature 

readings from sensor networks is that - [alpha-1 over log n]. 

The architecture for that is the commonsense architecture. 

If you have a bunch of nodes, you break them up into cells 

and you tessellate them. In each cell, you add up the 

temperatures, you sum the temperatures, and then you 

propagate all the sums along an entry route at the collector 

node, and that is the commonsense thing that anybody 

would do. 

However, it turns out that if you want to compute the max temperature, not the average, then you can do it 

exponentially faster. The rate at which you can do it is [1 over log log n]. I just want to show you how you could take 

advantage of what you are computing. You can take advantage of what is called block coding. In other words, I do not 

compute the maximum temperature every day but I gather together a bunch of temperatures and then spew out a 

bunch of maximum temperatures. 

Just to show you the idea, let us suppose that all temperatures are binary, 0 or 1. So anybody who has a temperature of 

1, has a maximum temperature automatically. Let us also suppose that we are all collocated so that, when I talk, 

everybody hears, and whenever anybody talks, everybody hears. Then the first node can simply announce the set of 

times at which it has a max temperature – so at times 10, 15 and 20, it has a temperature of 1. Then the second node 

can butt in and say, ‘Okay, I have a maximum temperature at these three times.’ Such information can be very efficiently 

compacted and therefore you can get exponential speed-ups. The way you operate these networks can be quite 

sophisticated. 

Knowledge of time important in Cyberphysical systems 

– However no two clocks agree 

– How to synchronize clocks in distributed systems? 

In computer science, beginning with the work of Cook in 

Canada, that leads to this whole theory of complexity, and 

we need similar theories of complexity for sensor networks 

– in fact, for all these cyberphysical systems. 

Clock synchronization in distributed systems 

^ 

x 01 

^ 

x 12 

^ 

x 23 

^ ^ ^ ^ 

v 3 = x 01 + x 12 + x 23 

Std. Dev of Error 

Can we do better? 

Let me turn to another theme, that of time and clocks. 

It turns out that a knowledge of time is important in 

cyberphysical systems. If computers are just talking to each 

other, their conversations could be purely event-based – 

time is irrelevant. However, when you are interacting with 

physics and physics-based systems, time is important 

because if of two of us were at the same spot at the same 



time, we would collide. Knowledge of time is therefore important in cyberphysical systems. What these things do is 

that they presage a movement towards not just event-based computing, but time-cum-event-based computing. 

However, no two clocks in the world agree and the question is, how do you synchronise clocks? What are the limits to 

synchronisability? The traditional approach to clock synchronisation is really simple. Let us say that this is your route 

clock, and here is your network, and then these two nodes talk to each other. Essentially, this clock finds out how much 

ahead of that clock it is, the offset, and then these two clocks talk to each other, with this one saying, ‘I’m this much 

ahead of you’, and so on. This node [on slide] then finally adds up all these offsets and gets its estimate of time and 

perspective as well. 

Spatial smoothing in random networks 

Random multi-hop network n nodes 

– Common range for network connectivity 

– Multiplicity of paths can reduce error 

– Distributed algorithm 

Theorem: 

Synchronization error can be kept bounded in large wireless networks 

– Lends support for the feastibility of time-based computing in large distributed 

wireless 

It turns out that each of these conversations is a little noisy 

and so a certain error is introduced. Basically, the standard 

deviation of the error is the sum of the errors along the 

diameter of the graph, if you will, which grows like the 

square root of the diameter. If there are n nodes arranged 

in a plain, then the diameter is [square root n] and so 

basically the error is growing like [n to the one-fourth]. 

This means that, in a large network, your synchronisation 

error will increase and that is not good if you want to build 

applications. So can we do better? 

(Giridhar & K ’05) It turns out that you can, and I just want to show you an 

15/34 

idea. Let us suppose that I have a random network, and 

suppose that all nodes choose some range with which the network is connected. In a connected graph, there is a 

multiplicity of paths from one node to another and you can average out the errors over all these paths and actually 

build very simple distributed algorithms so that – and this is a fundamental result – the standard deviation of error is 

bounded. We can actually prove that we can keep synchronisation errors bounded in large networks of arbitrary size. 

That lends support to the feasibility of time-based computation in wireless networks. 

Object tracking by directional sensors 

Object 

moving 

at constant 

velocity 

Domain 

Directional Sensor 

Sensor locations and directions are unknown 

Object locations, tracks and speeds are unknown 

Only times of crossing are known 

Goal: Estimate trajectories od all abjects as well as all sensor lines 

– Optimization problem is highly non-convex 

– Use adaptive basis tuned to motions of the first two objects 

(Plarre & K ’05) 16/34 

Let me show you one application of tracking an object 

purely through measurements of time. We have a domain 

and let us suppose that, in that domain, I throw down a 

highly directional sensor which could be like a laser beam. 

Whenever anybody trips the laser beam, I record the time 

when they crossed the laser beam, so I have time 

measurements of crossing – but I do not know where the 

object crossed, in what direction or at what speed. I do not 

know any of those things – just the time. 

Let us suppose that I randomly throw down a bunch of 

such directional sensors, and that objects cross the domain 

at constant speed. So this object crosses and, as it crosses, 

I get the measurements of the times of crossing. Then there is another object that crosses and, again, I have 

measurements of time of crossing and so on. These objects would be moving at different speeds but each object has a 

constant velocity. Let us suppose that everything about this network is unknown – I do not know the sensor locations 

or directions, I just ‘air drop’ them. I do not know about object locations, tracks, speeds – none of that, but only the 

times of crossings are known. However, I want to estimate everything – I want to estimate the positions of all sensors 

and of all objects and everything. 

Of course, it is impossible to solve this problem because we have to agree on a co-ordinate system – so we can solve it 

up to a co-ordinate system, but all these co-ordinate systems are equivalent. 


Implementation with laser pointers, motes and Lego car 


I want to show you an application and there is another 

reason why I have introduced it. It turns out that these 

kinds of technologies will have a fundamental impact on 

our university curricula. This is a particularly simple 

experiment which requires minimal hardware to set it up – 

in fact, it uses paper cups, a Lego car and these laser beams, 

and a few of these Berkeley modes, as you see. 

[Shows video – model vehicles in lab] 

You have these Berkeley modes and these paper cups and 

you have a small Lego car with a little flag. When the flag is 

up, it trips these laser beams and when the flag is down it 

does not. You just move it up and down the domain. 

Initially, I was a little sceptical about whether this experiment would work, given the possibilities for numerical error, but 

I was surprised. If this is the actual path of the object, these black dots indicate the estimates. Also, the system picks up 

how the laser beams are pointed. I believe that similar things should find their way into our curricula at universities. 

The third generation of control systems 

Let me move on to control, and set the historical stage here. 

We are at the cusp of the third generation of control 

systems and so, if we think of the first generation of control 

systems as analogue control systems, the technology for 

that was electronic feedback amplifiers. The technology 

created a great deal of need for theory, which was 

admirably met by people like Bode, Evans, Nyquist and so 

on. In fact, there is a beautiful book on the history of 

technology by a professor at MIT, David Mindell, which 

shows how the fields of computing and communication 

control all arose together about 60 or so years ago. 

Starting in about 1960, we had the second generation, 

which is digital control. This was when digital computers 

came along, and you could do a little computation before you closed the loop. I believe that people like Rudy Kalman 

and so on happened to come along at the right time which needed a certain theory, which was a states based theory, 

and that was supplied by several researchers. 

At the computer science end, this technology was supported by developments in real-time scheduling which took 

place in some pioneering work in Illinois, with the work of Leonard Lewin. However, things have changed over the last 

40 years and computers have become much more powerful and embedded in all kinds of devices. The whole fields of 

wireless and wire LAN networking have come about and software has also become much more powerful. This is 

actually leading to a revolution which I call network embedded control systems. 

Challenge of abstractions and architecture 

I believe that the first and most important challenge for this dual technology is to decide what are the appropriate 

abstractions and what is the right architecture. Let me make the case for why abstractions and architecture are 

important for the evolution of technology. 

Let me start with the architecture of the internet – and many of you may be familiar with this. There is a layer in the 

hierarchy. If you are a person in communication theory who knows a great deal about modulation, then you would 

work on the physical layer problems here. If you were a graft theorist, you would work on the networking layer over 

here, and if you were working on HTTP or something, then you would work up here. So there is a hierarchical 

segregation of tasks.


This architecture, along with what is called peer-to-peer 

protocols – I claim that the architecture has been more 

important for the proliferation of networking, in comparison 



to the algorithms, even though the algorithms are very 

Presentation Layer 

Presentation Layer 

Source Channel 

Session Layer 

Session Layer 

Hardware 

Software 

Coding Coding important. Why do I say that? By the segregation of tasks, 



Network Layer 

Network Layer 

we guaranteed that each of us can work on our little 

Data Link Layer 

Data Link Layer 

Pshyical Layer 

Pshyical Layer 

specialty and, when we put them all together and compose 

them, the interfaces have been worked out so that the 

whole thing works. Not only that, but this layering also 

gives this technology longevity. Over the course of time, 

therefore, you may have a different and better idea on one 

of the layers – let us say TCP. Then, you do not need to 

replace the whole stack but you just replace that little sliver 

of it and the rest of it can work. That longevity allows this 

technology to evolve and the longevity also facilitates proliferation. Proliferation drives down the cost per 

implementation. 

The point I want to make is that there is always a tension between architecture and performance people, because 

performance people always want to bust architecture. They want to take short cuts – they say, ‘Gee, if I could just 

expose parameters of this layer to this layer, then I could improve this by 10 per cent.’ However, at the back of the room 

there could be another person saying, ‘Wait a second! If I expose these parameters to this one, I could do 15 per cent.’ 

If you start implementing all of these short cuts, however, in the end you will have a spaghetti architecture – which will 

mean no architecture at all, and it will be hard to maintain and to upgrade and so on. You may have a faster system, but 

you will not get a million of them. So, even though there is an apparent tension between architecture and 

performance, I contend that architecture is also performance oriented, while keeping in mind the long time horizon. 

Another example that I like very much is due to Les Valiant at Harvard. He claims that the success of serial computation 

is due to the von Neumann Bridge. The way to think about it is that you have Microsoft and Intel and they do not need 

to talk to each other but, as long as they conform to a vague abstractional on the other side, their products by and large 

will inter-operate. That has been the reason why serial computation has been phenomenally successful. 

In contrast, parallel computation has no von Neumann Bridge. It is very hard to separate architecture from algorithms 

and that is the reason why there has not been proliferation. Similarly, in communication, there is the separation 

between source coding and channel coding – source coding can be done in your JPEG, or you may do it in software, 

whereas channel coding may be done in your network interface card, and so on. This is Shannon’s result, and so on. 

The point is that we are now getting into very complicated systems where we have communication control, serial, 

parallel, everything. What are the appropriate abstractions and what is the architecture? What is the goal here? 

The critical resource is not the cost of the equipment but the critical resource is the designer’s time – your time and my 

time. When projects go into over-runs, it is not because something is a little too expensive but it is usually because 

there is something wrong in the whole design. Our goal therefore is to make it very easy to enable rapid design and 

deployment. Standardised abstractions and architecture 

help, so we can just build these things like levels and 

therefore enable proliferation. 

Information technology convergence lab: 

the systems 

Let me show you some efforts that we have in our lab. 

We have these model cars running around on this plywood 

sheet, with these cameras up in the sky. There is image 

processing going on here. There are all the levels of 

decision making – set points, tracking, scheduling, planning, 

re-planning, re-scheduling and so on. You may not be able 

to see it on the slide, but there is a wireless ad hoc network 


here of laptops, and all these laptops are controlling the cars. This is a completely closed-loop system - it is closed over 

vision and it is closed over wireless networking, but what I want to focus on is the fact that it is closed over middleware. 

I will explain what I mean. 

IT convergence lab 

Let me first show you what we can do in this lab. 

[Video shown – model vehicles in lab] 

That is the interaction between logical dynamics and 

differential dynamics. This is a pursuit evasion scenario, OJ 

Simpson style. There is a car being driven by my student 

and these other two cars have to follow automatically in 

formation, and he is trying to confuse those two. 

[Video continues] 

http://decision.esl.uiuc.edu/~testbed/videos/Overall_Long 

Abstraction of virtual collocation 

The first abstraction I want to propose is what I call ‘virtual 

collocation’. What do I mean by that? Here, we have the car 

and the actuator, which could be the gas pedal, steering 

wheel or whatever. Then we have all the layers of decisionmaking. 

Then there are the sensors, and you have more 

than one sensor, so you have a server and data fusion 

because you have lots of cars. Then, of course, you need to 

supervise all of these and so on. If you ask a control 

designer to design directly for this very complicated view of 

the system, it is a difficult task because the notion of time is 

different at different nodes, and the notion of IP addresses 

is different. 

There is a great deal of detail which someone needs keep 

track of. What I want to do is to reduce this complicated 

system to an input/output view. If you go back and ask an electrical engineer what architecture is, they will probably 

say block diagrams - interconnecting by lines and block diagrams and that is architecture. It is the whole notion of 

signal flow graphs. What we want to do therefore is to reduce these complicated software systems to such 

input/output loops. 

The abstraction layers 

How do we do that? We do that through middleware – let 

me explain. Here, we have the system and the first 

abstraction that we have is that of a node – everything we 

call a node. Then the link layer creates the illusion of links. 

The networking layer clears the illusion of a graph – the 

notion of connectivity, enter and connectivity. 

The transport layer, for those of you who know 

communication, creates the illusion of pipes, so if you 

drop a file here, it shows up there and you do not need 

to worry about the graph any more. 


We are moving from nodes to graphs to pipes and so on, 

and then next natural thing I contend is just to think of the 

whole system in its entirety, as a collocated system, not 

variable to the complexities of interconnection and the way


you would design applications for it is through component logic. If you are a Kalman filtering expert, you write a few 

lines of equations, which sit as a Kalman filter. If you are an image processing expert, you write an algorithm for image 

processing or deadlock avoidance, or whatever. The middleware, which I shall explain, will take care of how all these 

components are operated at these nodes. So you try to hide the complexity of the system from the designer and you 

allow specialisation – and the middleware manages the components. If the network layer is created by some version of 

distribution Bellman-Ford, and the transport layer is created by TCP, the virtual collocation layer is created by Etherware, 

which is our version for the middleware that we have developed. 

I should say one other thing. Clock, for example, could be a service, and so an application will use the facilities of a 

virtual collocation layer and also specialised services. For example, the set of cars on a street could be a service which is 

composed out of other parameters. 

Component migration 

Let me show you an application – component migration. 

Let us suppose that we have a camera here which is 

generating pixels. You could ship all these pixels from this 

camera to this computer but then you may stress the 

communication link. On the other hand, you might ask, 

why not just compute just the latitude and longitude at the 

camera and then ship those co-ordinates over, thus 

reducing the data bandwidth? However, that would stress 

the relay processor, so which should you do? 

That is exactly the kind of detail that you do not want the 

http://decision.esl.uiuc.edu/~testbed/videos/migration.mpg designer to worry about because, after all, it can change. 

If you replace your camera with a more sophisticated 

camera, or your network with a better network, the decision 

point to change. For example, if your Kalman filter is 

running on this computer and generating excessive overhead, then you would like the Kalman filter as a component 

automatically to take its stead and migrate over. 

[Video shown – models in lab, middleware migration] 

So basically, we are changing the engine of the car when it is running. This kind of facility is very useful because the 

steady state of all large systems is that there are failures in some way or another. You want the system to operate and 

function in those failures and so, for reliability, you need these kinds of mechanisms, which we are providing easily to 

the control designer. 

System-wide safety and liveness: automatic traffic control 

What about theory? It turns out that we need theory. 

This is a traffic control example. There are these traffic lights 

in streets that you cannot see and the cars are supposed to 

obey those traffic lights politely, which they do on occasion. 

[Video – models in lab] 

There is a traffic light there, and that car is in a rush. So that 

is the kind of application. 

http://decision.esl.uiuc.edu/~testbed/videos/city_7ears.mpg 

If you want to design that kind of an application, there is a 

great deal of complexity underneath it. For example, this is 

a graph of concurrency at the traffic light. All things can 

happen at the traffic light and, to reason about this entire 

system, we have to discretise the entire domain, and that 


adds a great deal of discrete complexity. In computer science, we are dealing with these discrete calculations, 

interfacing with the physics of the car, so those are called hybrid systems. We ultimately need proof of safety of these 

hybrid systems. 

This is a Mickey Mouse answer of a kind of theorem, just to illustrate the point. Imagine a directed graph, and here are 

some properties of the graph. Imagine a number of cars, some properties of the environment, road width and so on, 

and the angles of intersections. There are also some models of the car and some notion of real-time scheduling. We 

can then guarantee that all these cars could be operated without collisions, safely, and without gridlocks, liveness. 

This is a very simple, hand-crafted proof for this application but, as we design very complicated systems, we will have to 

automate these kinds of proofs of safety and so on, and that is a huge challenge for theorists because complexity is a 

huge barrier. 

Collision avoidance 

I want to show you collision avoidance. It turns out that, in the US and elsewhere, hundreds and millions of dollars are 

wasted on collisions, and injury from collisions. 

[Video – model vehicles in lab] 

In the town of Champaign, where I come from, people pay money to see these kinds of events. The point I want to 

make is that most accidents are caused by human error. In fact, if you could just have someone tap you on your 

shoulder two seconds before, you could prevent many accidents. In this day and age, we should not be having these 

kinds of accidents. That is the first point. 

Secondly, it turns out that designing systems with the human being in them is actually more difficult than designing 

automatic systems. If you automate things, you can actually do a little better. 

Intelligent intersections 

The oncoming pedagogical challenges 


The next topic is intelligent intersections. I realised, after 

spending a day here, that I am probably talking about the 

wrong topic in the wrong place because you already have 

better technology with roundabouts – you do not have 

these intersections. It turns out that stop lights and traffic 

lights are very wasteful. For example, in suburban roads at 

intersections you often stop when there is no need for you 

to stop – and in some countries they do not – and this also 

applies at night. The idea therefore is that we should just 

get rid of these altogether. We can then probably lower fuel 

consumption, reduce delays, create greater safety and so 

on. This is an application and I want you to decide for 

yourself whether you would sit in one of these cars – there 

are no lights, but they just negotiate packets and cross the 

intersection. [Animated diagram] There are obviously 

significant legal and social challenges here, and perhaps 

psychological ones too. 

This is my last slide. It turns out that the convergence of all these technologies is giving rise to pedagogical challenges 

which we, at universities, have had to confront. We live in this post-Maxwell, von Neumann, Shannon, Bardeen-Brattain 

world, and we can do rather sophisticated things. I believe that the 21st century is the age of large system building. As 

we recognise the era of limitations – environmental, energy and so on – we will be building smart transportation 

systems, smart energy grids and so on. 

If you look back over the last 50 years or so – and perhaps you should never trust an account of history so soon after the 

event – you could argue that the last 50 years was the age of building strong individual disciplines. For example,


computation is about 60 years old, and modern control is 

about 45 years old. Communication – with Shannon – is 

about 60 years old, and signal processing, Cooley and 

Tookey, is about 40 years old, and so on. However, we are 

now seeing a unification of all these things. For example, 

even the simple problem of calculating the average 

temperature in a sensor network – is that a communication 

problem? No, not completely, because you also need to do 

computations. Is it a computation problem? No, it is 

communications also. 

You can see that all these fields are coming together and 

somehow we need to communicate the totality of all of this 

to undergraduate students. At the same time, if you want 

to do research, you need a deep knowledge of these individual fields and the question is, how will we meet all these 

challenges? I will stop there. Thank you. 


Questions & Answers 

Mike Walker: Thank you, Professor Kumar, for that fascinating talk which took us from ad hoc networks, radio networks, 

through cars changing their engine while still moving, to traffic control and collision avoidance systems. 

Professor Kumar has agreed to take some questions. Let me start because, in our business, which is based on cellular 

radio systems, they are all very old-fashioned. It is that very old spatial diversity planning scenario that you painted right 

at the beginning. You showed that in fact Maxwellian networks is the way we ought to look at things, and this is the 

best possible. However, we have seen many attempts to build ad hoc networks with direct communication from one 

mobile device to another. These have all more or less failed commercially. Do you have a feeling about why that is so, 

and whether there will be a turning point so that we will see some of these networks being deployed commercially for 

real? 

PR Kumar: There are two answers to that. If we look at the pace of evolution of communication technology, it is just 

amazing. Telephones are about 100 years old, cellular phones are about 35 years old and the internet is about 25 years 

old. Who knows what it will be like in 20 years from now? There could be an information fabric connecting individuals 

and so on. One cannot rule out such things, and we may see them in the future. 

One of the issues has been what is the application of these ad hoc networks. Of course, the military is always hungry for 

any application or any technology but what about in the civilian world? There have been some applications and, for 

example, when Hurricane Katrina struck New Orleans, there was actually a team from Champaign-Urbana Wireless who 

went down there to set up the emergency network without any infrastructure, so you have seen those kinds of things. 

One big way it could potentially take off would be in vehicular networks. In the US, there has already been spectrum set 

aside for vehicular networks. Those are systems with some structure, when cars go along the road and so on, so that it 

is not completely unstructured. This actually facilitates people who are trying to design systems, because at least they 

have a target in mind. People are thinking of safety applications, infotainment applications, highspeed tolling and so on. 

I think vehicular networks could be a domain that you will see being realised sooner. 

Professor Lajos Hanzo (University of Southampton): I very much enjoyed your lecture and you set out a number of 

interesting challenges for us. One of these is in the field of cross-layer optimisation. We set up the seven-layer OSI 

architecture and it is very convenient, as you said, to have our little systems optimised on a layer by layer basis, but of 

course mobile communications does not quite fit into that mould. For example, we have power control and all the 

related functions which are stuck to the side of the seven-layer architecture. 

You then went beyond that and spoke about these complex systems where we now integrate control, communications 

and even mechanical systems. You also provided a very interesting architecture for that. However, in a way, you are still 

also suggesting that perhaps even these complex structures will have to use some form of cross-layer optimisation as 

well as some form of logical ordering of the different functions into a greater entity. Do you have any comments on 

this? 

PR Kumar: Some of the theory that I talked about earlier clearly ignores multiplicative cost – so that factors of 200 or 

300 are irrelevant in these theories. You are searching for an architecture for a Maxwellian network in this infinite 

dimensional space, whereas there are all kinds of possibilities. The theory gives you some guidance on what the 

architecture is but of course in the real world we want to improve performance by factors of two, three and so on. 

A great deal of design work is being done and so, in that sense, there is a little bit of a disconnect between the 

architecture that this theory says, and the real world. 

A very good example, as you mentioned, is power control. Power control is, how loudly should you talk? When I send a 

packet, I can decide at what power level to transmit it, and that has all kinds of implications. For example, if you think 

that the power level is affecting signal quality, then that is a physical layer issue that classical communication engineers 

are worried about. On the other hand, when I talk really loudly, it causes interference to somebody else, and 

interference is treated at the condition control layer of the transport layer, which is somewhat higher up. On the other 

hand, power control also affects connectivity and so, when I talk loudly, I can get to my final destination in three hops 

rather than in 30 hops if I were to talk softly. That affects the network layer. 



Power control affects all the layers and the question is, where should you address it? That is actually one of the most 

difficult problems there. It is not sufficient to say that you will address it all over the place because then different layers 

would be fighting with each other and turning knobs. We still do not have any satisfactory answer on that and, even in 

communication networks, we are still in research mode. 

Turning to these more sophisticated systems, they are in the very beginning stages of this and what I have just spelled 

out is one proposal. I think there will be further evolution of thinking and competing proposals and so on. However, it 

is true that I have suggested a kind of layered hierarchy, if you will. 

Sreebhusan Ghosh (AT Consultancy): I have one question for Professor Kumar with regard to the practical application 

in poor countries. He mentioned earlier that mobile phones have taken over like fireflies in India and China – I think that 

in China, 60 per cent of the population have mobile phones and it is rapidly progressing in India. I was very surprised at 

how quickly it has taken off because five years ago there were hardly any but now there is the better part of nearly 20 

per cent, for which Mr Sarin of Vodafone spent a great deal of money for a network in India. 

The point in question is this. Seeing that the mobile phone technology works so well, despite the relative level of 

ignorance and lack of technological development, do you see any particular application with this networking, also 

without any land line involved, which will help the traffic system in major cities like Calcutta or Bombay, where at any 

given time 50 per cent of the traffic lights do not work because of communications alone? Or likewise, in big cities in 

China or elsewhere? Or do you think that the technology itself is so complicated, comparing from the mobile phone to 

mobile networking, that it is a long time before this takes place? 

PR Kumar: Interestingly, these new technologies that we are seeing allow countries to leapfrog the industrial 

revolution. Actually it is a paradox: less developed countries probably have more wireless infrastructure than developed 

countries, because developed countries have so many wires in the ground and the capital is already there and it is hard 

to compete with that. 

There are many applications, for example in remote medicine. In the villages in India, as you mentioned, if you can 

transmit the image of your skin or whatever, then a doctor could at least do some preliminary diagnosis. There is 

greater justification for using these kinds of technologies in less developed countries than in developed countries where 

there is an infrastructure. 

There are also other applications, which I should have mentioned in answer to Professor Walker’s question. In hospitals, 

every time you are hooked up to all these instruments in the emergency room, with these all these wires trailing 

around, we can start to interconnect things wirelessly. Those kinds of applications, regardless of whether it is the US or 

India or wherever, mean that there is a great deal of potential. For traffic, the answer would probably have to lie in mass 

transit. 

Professor Ralph Benjamin (University of Bristol and UCL): Early on in your talk, you pointed out that, in a cellular 

network, frequency reuse with minimum interference benefits from a rapid increase of attenuation with range. 

The scope for doing this is rather limited but one can do a little by choice of frequency. Do you have any views on an 

appropriate combination of frequency reuse and time reuse, in order to minimise interference? 

PR Kumar: At high levels, there is not much difference between the two, or even CDMA. These are all ways of 

orthoganalising your channel, that is breaking up your overall channel into pieces – whether you package them in 

blocks of frequency, blocks of time or blocks of codes or whatever. At a high level you are just partitioning your 

resources and so there is not that much of a difference. Of course, there may be differences in other kinds of ways, for 

example perhaps CDMA may allow softer entry into and exit from the system and so on. At a high level, however, there 

is not much of a difference between the two, fundamentally. 

Mike Walker: Your traffic control is fascinating. Do you think we will ever reach the stage where people will really trust 

systems that will enable them to zoom across crossroads, seemingly without paying any attention whatsoever? 

PR Kumar: Very often, what we are familiar with is very comfortable, while we think that what we are not familiar with 

is just impossible. We seem to be on that edge all the time. However, the technology is already coming where you 

have given up the longitudinal motion of your car with cruise control – so you already do such things. I guess that 

lateral motion is the next step. 


Human beings will also evolve and we will have to adapt to these new technologies. Of course, there are all kinds of 

challenges and not just us adapting – there are also legal challenges and so on. I do not want to minimise the 

challenges that exist, but there is the potential. 

Mike Walker: They make superb games anyway. Your students must love them. 

Professor Fu-Chung Zheng (University of Reading): I would be interested in the clock synchronisation progress that 

you mentioned. Some of us know this phenomenon, which happens in the forest in some Far Eastern countries, which 

is that hundreds upon thousands of bats would flash together during in the night, like fire blocks, and they have a really, 

really intricate synchronisation mechanism between them while we, as human beings, have to use other tricks as you 

have just mentioned – averaging and so on. How are we doing compared with those bats? The real question is about 

the accuracy that we can achieve now – it is milliseconds or nanoseconds? 

PR Kumar: The last question is always easier. The most we can achieve is 6 microseconds. There are many things that 

biology does which we cannot begin to get close to, and vision is a good example of that. Even the way that bats can 

spatially locate something that is less than the resolution of the neural spike – I do not know. We still have much to 

learn from biology. 

Dr Graham Woodward (Toshiba): [Without microphone] This relates back to the shared bridge network. So much of 

our feedback system is motivated by underlying information theory and you made an interesting observation on 

capacity by taking a Maxwell view rather than a virtual view of the network. I have seen the result of experiments based 

on unicast users collaborations. Network coding shows that you can get enormous capacity by collaborative coding 

across the network, especially when there is unicasting and broadcast. Is there a network coding theory emerging for 

Maxwell’s view of the network, and what does that tell us about networks taking a Maxwell view rather than a virtual 

view 

PR Kumar: That is a good question. As far as unicast systems are concerned, the information theory allows for network 

cording or anything else. It is an absolute theory, but it is only up to three constants, as I mentioned. On the other 

hand, there are simple examples where, when you are relaying packets in opposite directions, then you can use network 

coding to give a certain factor improvement and so on. So network coding definitely buys you constant factors 

improvement. 

The one thing I did not touch upon is multicast, where network coding has a great deal of potential. 

Ralph Benjamin: Concerning the intelligent crossroad junction, to operate intelligently, clearly you have to monitor the 

traffic approaching from all sides, and have distinct lanes for turning and keeping straight on, or other indication of that. 

Subject to that, you could give each block of traffic a target velocity with tolerances, which normally allows continuous 

flow and, in a limited addition, these target velocities can go down to .… In the present system, the lower limit of 

intelligence can no longer improve things. 

PR Kumar: Our system works on something like that, with the added feature that there is a proof of safety. The proof of 

safety is impervious to whatever the car in front of you does, subject to the limitations of Newtonian mechanics. It is 

that kind of system. 

Mike Walker: If there are no further questions, I suggest that we move into the Marble Room for drinks. I would like to 

thank Professor for his excellent presentation and the very interesting discussion that followed. [Applause] 



The complexity and the promise 

of a technology and 

service-neutral future 

Friday, 3 October 2008 

Speaker: 

Chair: 


Associate Professor Department of Electronic & Electrical Engineering 

Trinity College, University of Dublin 

Professor Mike Walker, FREng 




Professor Michael Walker: Good evening, ladies and gentlemen, and welcome to the second lecture in the third 

series on mobile communications and networks, which is jointly sponsored by the Royal Academy of Engineering and 

Vodafone. For those of you who do not know me, my name is Michael Walker and I am responsible for research and 

development for the Vodafone Group and I shall be chairing this evening’s meeting. 

This is our second lecture in the third series and tonight we have invited Dr Linda Doyle from Trinity College, Dublin, to 

address us. She is in the Electronics and Electrical Engineering Department, and I guess that most of our academic 

visitors here come from similar departments. She heads Emerging Networks Research in a centre with the interesting 

name – one I had not heard of until now – The Centre for Telecommunications Value-chain Research, so this is 

something new for me at least. It is a multi-disciplinary centre, so I guess it has engineers, economists and perhaps 

some social scientists, all looking at a subject which is central to my existence at least, and to that of a number of others 

in the audience. 

Linda’s team specialises in spectrum access and reconfigurable networks and she also has an interest in art and 

technology, although I do not know whether she will talk about that this evening. That is a subject which has also 

recently been of interest to a couple of people in the research group in Vodafone. Frankly, it has not made much 

traction in the company as yet but there is a growing interest in art and technology. I do not think it is like Ray’s art, 

which means that he paints as well as being a first rate technologist. 

Tonight, Linda will address us with a lecture entitled ‘To the edge of chaos: the complexity and promise of a Technology and 

service-neutral future.’ 



The complexity and the promise of a technology 

and service-neutral future 


Associate Professor Department of Electronic & Electrical Engineering 

Trinity College, University of Dublin 

I am honoured and also quite humbled to be here, because the lecture I shall give touches on a wide range of topics 

and I am very much aware of your huge expertise in the individual products. This is a great opportunity to be here and 

discuss some of the ideas with you. 

I want to talk about spectrum and spectrum management. Spectrum is the life-blood of any communication system 

and it is very dear to my heart. I will go through a few of the ideas about spectrum management with you today. I will 

start by talking about how spectrum management has been questioned in recent years and what is currently 

happening in the topic, before I move on to some of the ideas for the future of spectrum. 

You will recognise this as the sinking Titantic. The loss of the 

Titanic was a major catalyst in what became what we know 

as spectrum management today. When the Titanic sank, 

boats that were much nearer when the Carpathia came to 

help did not actually receive the distress signal from the 

Titanic, so chaotic were things at the time. This acted as a 

catalyst to encourage governments, particularly in the United 

States and around the world to think of a spectrum 

differently, and to organise how spectrum should be 

managed. It was no longer a right to transmit, but you 

actually had to be granted that right by the authorities. 

So this was very much a catalyst in how things began. 

This diagram represents where we are 

today and how the vast majority of 

spectrum management takes place. 

What happens currently is that some 

international body, like the ITU, broadly 

defines what services and frequencies 

Frequency Band 1 : 





Mobile Services 

Broadcast Services 

Fixed Services 

Mobile Operate A 

Mobile Operate B 

should be used for what purposes, and 

Site licensed & managed by the regulator 

Site block licensed & managed by the operators 

what technologies should be used to 

deliver that. Then, on the more 

Source: http://www.ofcom.org.uk/consult/condocs/sur/specturm/ 

national level, that picture is refined 

and then a spectrum is assigned, in various different ways, to those who want to use it. So the way it is currently 

assigned tends to be based on first-come, first-served, right up to much more complex options, where a companies like 

Vodafone and O2 bid for 3G spectrum and everybody is probably familiar with some of the options they have had in 

recent years. 

Unused - Guard Band 



People very often refer to this approach as an administrative one, or you often hear the term ‘command and control’. 

This emphasises the fact that this is a quite centralised approach, where someone on-high decides what will happen to 

the spectrum – what services will be used in those particular bands, and then people react accordingly and do what 

they are told. In the US, you often hear people talk about that ‘Mother, may I?’ approach, where you have to ask 

permission to do things and you do not take the initiative. 



ComReg Collection - Start 16/Apr/2007. 18:02:30. Stop: 18/Apr2007, 12:09:00 


Source: Shared Specturm Company (http://www.sharedspecturm.com/) 

NYC Measurements 31- Aug-2004 15:15:41 

NYC Measurements 31- Aug-2004 15:46:09 

What is very attractive about the approach is that it allows 

us to manage interference very well. Regulators are able to 

model and understand how communications are likely to 

interfere with each other and tailor licences accordingly. 

So, you can put power into licences, and you can also 

stipulate where guidelines are, so that that does not 

interfere with the rest of it, so life is quite organised and it 

is very attractive from that perspective. 

The downside of this is that many people feel that this 

system is one, and first of all that it is not very responsive to 

new technologies and changes. Secondly, you are forcing 

regulators and authorities to pick winners. There are some 

fantastic examples of where winners have been picked 

really well. If you look at what happens with GSM, and at 

how harmonisation across Europe occurred and how the 

GSM network and service has developed, that is fantastic. 

However, there are other examples – for example in the EU 

– where we are all directed to put spectrum aside for 

applied specifically for urban paging technology, and that 

never came into being and the spectrum sat there, idle. 

So the picking of winners is a kind of ‘wise man’ approach, 

and it is part and parcel of the vast majority of spectrum 

management that we have known to date. This need to 

pick winners and the slow responsiveness to new 

technology is something that people are seriously 

beginning to question. 

Another thing that people question the arises is the 

question of spectrum scarcity. I do not know whether 

anyone here has ever looked at those very colourful 

spectrum allocation charts, where there is no space for 

anything else – the spectrum looks ‘full’. This has been 

hugely challenged in the past, and part of that challenge 

has resulted in these kinds of measurements. 

If you just concentrate on the middle part of this slide, the 

part that shows frequency usage, you can see what is going 

on. They are a bunch of frequencies, and this is time, and 

the blue means a low signal, while the red means a really 

busy, high level of signal. You can see that there is a good 

deal of spectrum that is completely unused all the time, or 

spectrum that is perhaps unused at night time – the time 

here corresponds to the night time. So people are saying, 

‘Okay, there is the spectrum around. I want spectrum – 

I have a new idea and want to innovate, but I can’t get any, 

but these measurements are showing me that free 

spectrum exists. 

This is a similar measurement, taken by this company called 


the Shared Spectrum Company in 2004. The measurements 

on the previous slide were also taken by this company. The reason why I have included these is because, very 

interestingly, these were taken in New York City during the Republican Convention at the time. A whole range of 

measurements were taken and not just one set of conclusions here. Despite the fact that it is a really busy city and a 

really busy time, there is still evidence in very many places that the spectrum is not being used extensively. 



The complexity and the promise of a technology and service-neutral future 



As a result of these kinds of measurements, many people 

have asked why we can’t do different things. Why can’t we, 

to a certain extent, ‘squat’ in the spaces that are empty? 

People talk about overlay approaches, where you find a gap 

in the spectrum and you temporarily use it, or here, for 

example, you might just use the spectrum at night time 

and then give it back to the main owners during the course 

of the day. They also talk about underlay approach, where 

you sneak in under the signal in such a way that you are not 

going to adversely affect the other users. This concept of 

dynamic spectrum has been very much on the agenda in 

recent years. People are saying that they are not happy 

with how the spectrum is managed and they ask why we 

can’t have this dynamic approach. 

The story does not stop there. As most people will know, in the world we currently live in we have digital TV coming 

into effect soon, and analogue TV will have to be switched off by 2012. The dynamic spectrum story and the use of 

what we call ‘white spaces’, or TV white spaces, is very on the agenda because of the move to digital TV. 

The New American Foundation has carried out analyses in various different cities around the US and they show if you 

switchover to digital TV from analogue TV, you will have a large amount of white space left over - so why can’t we use 

that? 

In the UK, you use the term ‘interleaved spectrum’ to refer to this white space and actually the UK is very forward-looking 

and Ofcom are considering the use of what they call ‘cognitive radio’ to make use of the TV white spaces here, which is 

quite an exciting development. These kinds of things of developments are continuing to push how ideas about how 

we use spectrum. 

And it is not just in areas where very few people live that there is lots of available white space, but also in cities like San 

Francisco and high density cities. The New American Foundation has done analyses across all sorts of different 

geographical areas. 

If we allow the use of white spaces/ interleaved spectrum, or dynamically use spectrum throughout the day, it would 

certainly lead to more efficient usage. 

However, there is another debate that has been ongoing since the fifties that encourages us to think of spectrum in 

property terms. Why can’t we decide that there is a set of rights that you can associate with spectrum (akin to property 

rights and which are tradable. Hence rather than stipulating that this spectrum has to be used to deliver a specified 

service, using a certain type of technology, why not let the spectrum consumer use spectrum as they see fit and trade it 

when they want to? 

A very famous economist in the 1950s, Ronald Coase, was one of the first people to question this. Since then, many 

economists have become involved in this debate and I usually find that, if you read any of the economists’ papers, one 

will say this is right and another will say it is wrong, but not necessarily support it with evidence. However, the main 

question, first, is whether spectrum is a scarce resource and, if it is, can we treat it as property, in a property-like fashion? 

Is it feasible, from a technical point of view, to consider it like property and to think about trespassing in terms of signals 

rather than in terms of trespassing on somebody’s property? And, if so, how should we go about it? So various 

economists and engineers have contributed to the debate 

over the years, including economists currently, like Tom 

Haslett, who is a very famous proponent of property rights 

for spectrum. Essentially, he argues that spectrum is scarce 

resource and those people who value it most should get it. 

On the other hand, there are those people who say that 

spectrum is only a scarce resource because of how we 

currently manage it, and that we should really consider 

more spectrum commons. One of the major pieces of 


evidence that people give in favour of this is approach is that they huge innovation took place in the ISM bands. 

The availability of unlicensed spectrum gave rise to a huge amount of innovation and a huge amount of growth in the 

wireless industry. 

The way that we typically define a commons today, is by some kind of power limitation, i.e. we do not permit devices 

that are unlicensed to radiate too much, so they can’t cause too many problems. However, the proponents of the 

commons argue that you could take a much more advanced approach and develop etiquettes and more complex 

ideas around how you can encourage behaviour through using a shared resource in a way that you all appreciate each 

other’s needs. John Crowcroft (computer scientist) and Bill Lehr (economist) wrote a very interesting paper on how you 

would go about thinking in a more advanced way about spectrum commons. This work is a really good example of 

technologists and economists working together and thinking through these problems. 

The big problem that people talk about when they talk about a commons is the notion of the ‘tragedy of commons’. 

Essentially the tragedy occurs when somebody behaves selfishly and overuses the commons resource to the detriment 

of others. 

This slide shows quite an interesting piece of work by artist Jonah Brucker-Cohen called Wifi Hog. In this work he was 

challenged this Utopian idea that wifi is a fantastic thing and easily available to all. You go to your hotspot and get the 

access you want. In Wifi Hog the system, as the name suggest, hogs the whole of the spectrum and stops other people 

from entering. This illustrates the concept of the tragedy of the commons very nicely. 

The overall point I am making here is that spectrum 

management has continued for years in a particular 

direction. Many people – and the number of voices is 

growing – are challenging the way we look at how spectrum 

is managed. Whether the challenge is from the point of 

view of taking a commons approach or from the point of 

view of property rights, or whether the focus is dynamic 

spectrum access the challenge is growing and this is a 

hugely exciting field of study. 

Spectrum management approaches are also being challenged from an application perspective. Here I have a picture of 

fire-fighters. Public safety spectrum is often considered differently from other spectrum – you cannot put a value on 

people’s lives – hence the spectrum for these services is very important. However, we now hear people talking about 

the notion of the ‘interruptible spectrum’. One example of this is when a public safety service provider uses gets access 

to commercial spectrum in emergency scenarios. Hence some of the spectrum resources are therefore transferred from 

the commercial users to the public safety users. Thinking from an application perspective helps think of how we should 

access spectrum. 

Let me move on to my Utopia, the way in which I think spectrum should be managed. To a certain extent, this takes 

many of the ideas already discussed and puts them together . 

To express this Utopia, I will use these diagrams that are 

based on the Rubik’s cube, which a couple of people will 

have seen and heard before. To a certain extent, they sum 

everything up in the best way of describing what is 

happening here. 

To understand what I am about to explain, you now need to 

think of spectrum from this kind of cube point of view. In the 

diagram you have frequency, space and time. The X,Y,Z 

coordinates of space are represented as one and I have 

placed some places around Ireland on the diagram. If we 

look at spectrum like this we can begin to see other things. 

For example, this could be Vodafone in Ireland, and this could 

be their GSM licence – the space between frequencies is 




exaggerated on this slide, for clarity – and this could be their 3G licence. What actually happens in many countries is 

that they have to pay, give over hard cash, to gain access to the spectrum they want typically long before the market for 

the product that uses the spectrum emerges. Hence in this case the operators were sitting on £g spectrum unable to 

use it until sometime later. Essentially, this is the picture of how things are now. 

And this is the picture of how things could be. We would like to take this cube and think that anyone can use any 

chunk of spectrum for whatever service they want, and deliver it using whatever technology they want. This slide really 

depicts a technology and service neutral future in which 

spectrum is tradable and can fluidly pass from one owner to 

the next. 

Think reconfigurable 

The other cubes in the diagram show some aggregation of 

spectrum blocks. Large chunks of spectrum become used 

for a particular service with a particular technology because 

the market demands that – not because of a decision made 

in advance. The technology and services that succeed come 

to the top, rather than somebody on high deciding in 

advance what those things should be. 

Of course saying that I know advocating the market place in 

the current times is not necessarily welcome! And of course 

there is always the danger – even though I am staying with 

Utopia for the moment – that this kind of thing happens 

and nobody wants it, and I suppose we need to recognise 

that. 

We can now add reconfigurability to the mix and see what happens. The technologies that are now emerging are 

adaptive and reconfigurable. With these in mind you can see how a very fluid future might emerge. 

Suppose I have some spectrum. I buy more, because I need to deliver a greater service to a greater area, and I want 

more frequencies. Then along comes a competitor. How can the competitor be accommodated? What we see here 

now on the slide are the spectrum ranges over which each 

entity can operate. I can operate over a much greater range 

of frequencies due to superior reconfigurable features and 

frequency agile hardware in my system. 

Think different scales 

What could possibly emerge is the following picture, 

where the really flexible entity sells some spectrum to the 

less flexible entity and reconfigures itself to use the 

remaining spectrum around it. Again, this is a very Utopian 

way of describing things, in nice neat boxes. But I am trying 

to present this whole idea of consumers using spectrum as 

they see fit and consumers making use of reconfigurable 

technology and hence opening up a different way of 

thinking about how services might be delivered, and what 

would happen if spectrum changes hands and is traded 

from one entity to another. 

You can also think of spectrum and spectrum management on different scales. At the beginning of this, with my 

Rubik’s cube, I just arbitrarily put in scales, and this timespan can be quite long – but you can begin to think of it, and 

take any individual block and sublet and sub-sublet it. 

The smallest time scale can represent ‘just in time’ spectrum. In the case of the larger blocks, you might talk about large 


chunks of spectrum where you are interested in more 

stability, where entities provide services for a longer time. 

In the case of the smaller blocks end-user devices that get 

spectrum on a per-session basis. It is very important to keep 

that kind of scale and timescale in mind – when you read 

things in this area, they become all jumbled into one 

timescale and different timescales enable different ways of 

working. 

Think different regimes 

You can also think in terms of different regimes when 

looking at these cube diagrams. If you look at any one of 

those cubes and think, ‘I am a spectrum consumer’, then you 

are not dictating how that spectrum within a cube should 

be used. The spectrum consumer can operate a commons within the cube for example or any regime they see fit. 

So this representation is a very general framework, to get people thinking more about a far more fluid way of dealing 

with spectrum than we currently do. 

Think more heterogeneously 

Finally, you could think more heterogeneously than I have depicted the story so far. I am not good at draw so I have not 

done this completely but essentially all of blocks do not need to have the same size, shape or timespan. 

The reason for using these diagrams is basically to pose 

questions about how we management spectrum and to help 

think about it in a much more fluid form. What, ideally, 

would that fluid environment look like, and how would we 

technical achieve this? 

I need to take a reality check now, because there are many 

challenges and difficulties in thinking like that. 

This is another art piece that I saw some time ago, called 

Digital Shelter, which was created by the artist, Pedro 

Sepúlveda. Essentially, the whole notion here is that you get 

a kit – that contains some kind of RF jammer – and you put 

the jammer down and you tape off an area around the 

jammer so that you can say, ‘I am free from mobile phone 

signals in this space.’ This is more conceptual art where 

people are playing with ideas. I supposes I have been 

speaking in these very neat terms myself up to now and 

acting as if transmissions of signals have nice neat borders. 

In reality, there is a huge amount of interference in the world in which we live. You can have adjacent channels, 

co-channel interference, intermodulation effects etc. If I take translate these concepts back into the Rubik’s cube like 

diagrams that I have been drawing, a far more messed up picture would result. 

So when we compare new and old regimes we see how you can control what frequencies are used where, i.e. 

frequency re-use distances and the co-channel interference can be managed when there is a single spectrum 

consumer. Whereas in the very fluid system you have random neighbouring blocks leading to a much more difficult 

situation. 

Again here you see how guard bands can help a situation in terms of adjacent channel interference – and are more 

easily planned when who is using what spectrum to provide which services with a specified technology is known in 

advance. 




DIGITAL SHELTER KIT Pedro Sepuiveda (1999) 

So as I said, there is an enormous amount of simplicity in the 

way I have described the initial diagram, which does not take 

into account the actual ‘mess’ that the signal actually creates. 

Most of the debate about anything to do with exclusive 

usage rights and the ‘propertising’ of spectrum has all been 

about how you define an entity, and how do you define 

those rights, in a way that takes those interference issues, this 

‘spill over effect’ into account. Many of the papers you will 

read will discuss those various suggestions on how that 

might be achieved. 

The following diagram captures the complexity of 

neighbouring spectrum consumers further. If I am deaf, and I 

am living in a house where the person next door plays extremely loud music but I cannot hear it, is that interference? 

Whereas, if I put a sensitive array of microphones around my house and the person next to me is playing extremely 

quiet music, and I am annoyed by that really quiet music, which of those two scenarios is depicted here? 

When it comes to thinking about mobile communication devices and wireless communication systems, you have to 

think the kind of situation encapsulated in this slide. That is why in this very, very fluid world, it is harder to define what 

kind of things can live next to each other. 

The problems do not stop there. There are enormous problems when you step back and begin to look at the market 

issues. People worry about fragmentation of spectrum, and people worry about entities buying spectrum to block 

others using it, and people worry about the cost of any of these ideas. A lot of people would say today – and certainly I 

hear people in industry say, the infrastructure costs are so expensive that the whole idea of perhaps installing 

something new and thinking differently is a big problem. 

There is another huge problem, and I do not know whether you have come across this. In the UK, if you ask someone 

for directions, they will typically tell you to go down the M1, take a left at the second junction and go on to such-andsuch 

a route. In Ireland, they tend to say things like, ‘Go to O’Brien’s pub and, after that take a left until you get to 

O’Donohue’s pub, and then take the second left when you get to McCarthy’s pub.’ – they think like that. The other thing 

they will tell you, if you ask for directions in Ireland, is, ‘Well, I wouldn’t start from here’, which is a typical reaction. That is 

the point of some of these ideas: we are where we are with the regulatory system that we have and it can be quite 

difficult to imagine how we can start from where we are now. A typical reaction is, ‘Here is how we would like things to 

be, but I would not start from here.’ That is something that needs to be overcome in this field. 

There are big challenges concerning interference, in how to define spectrum usage rights, in defining the regulatory 

policies and in the economic and financial arena. However, there is also a good deal of hope, and that hope comes 

from much of the engineering advances that have taken place in the last little while. In this part of the talk, I will focus 

on various different aspects of the technology that feed into that hope for the future. 

As I see it, it is not true to say that, collectively, any of the pictures represented here have been dealt with, but there are 

bits of advancement all over the place that are contributing to this picture and beginning to push things forward, and 

build on where we are going. 

I would like to spend a little time talking about cognitive radio. Thsi slides shows different radios, static fixed frequency 

radio, a multi-band radio, a multi-mode radio that we are very used to and a cognitive (software defined) reconfigurable 

dynamic spectrum enabled radios that supposedly can do any mode, any band, over a wide range of frequencies. 

There are probably a number of people in the audience who are very familiar with cognitive radio, but the term 

‘cognitive radio’ was coined by Joseph Mitola in the 1990s. He used this thing called the cognitive cycle, which depicts 

what cognitive radio was about. The whole idea is that you have a radio that has a brain, so that the radio has the 

capability of observing the outside world and then somehow making some decisions about how to react to that very 

changing and dynamic outside world. In this diagram from one of his papers, he particularly focuses on how you can 

react immediately and quickly, and how you can make long term plans about what to do next, make decisions and then 

act. There is a huge amount of research in the area of cognitive radio. 


As an aside, I was reading a few of the transcripts of previous 

lectures before I came here. I noticed that in Joseph 

McGeehan’s lecture, he was talking about software radio and 

cognitive radio as well, and making very interesting points 

about how a great deal of the technologies , when he 

designed radios in the 70s and 80s, had that kind of 

configurability in them. He made the statement that there is 

very little that is new under the sun. To a large extent, much of 

the technology that we see emerging is based on ideas that 

have been around for a while, or there are now techniques 

that allow those ideas to be put into practice. Cognitive radio 

is definitely the buzzword of the moment. 

Another way that it is useful to think about it – and this is the 

terminology that was coined originally at Virginia Tech in the US – is to talk about radio that has meters and knobs. 

A cognitive radio has a whole load of knobs, which you can set anyway you want, and you have some meters that are 

used to observe the outside world. You then have the brain which makes some kind of decision about how to set those 

knobs in the best possible way and in line with whatever observations were made with the meters. 

If you look at the literature on cognitive radio, nine out of 10 times, people talk about cognitive radio being used for 

dynamic spectrum access techniques. When you go back to the measurements that I showed when we looked at the 

overlay and underlay techniques, most people are interested in how you create cognitive radio to sculpt the signal to fit 

into one of those holes, or sneak the signal underneath the others. 

Acknowledging that, I want to talk about cognitive radio a little and then bring this back to the wider discussion about 

spectrum. 

Here is a cognitive radio that has lots of knobs. This is a busy slide with a great deal of detail on it but, essentially, in 

recent years people have designed every and any kind of software radio, with all parameters up for grabs. In this 

particular case, it is a kind of generic, multi-carrier CDMA/OFDM radio. By setting various kinds of parameters, you can 

turn it from one to the other or, by adding new components, you can make it behave in different ways. You can see 

plenty of examples of this kind of thing and, in this particular case, it is again focused on dynamic spectrum access. 

In this case there is a primary user which transmits a DBPSK 

signal, and there is the secondary user which uses DS-CDMA 

signal. It, the secondary user, wants to co-exist with this 

primary user, so it notices that it cannot co-exist in its current 

form. It adds another block into this system and, through 

doing that, it is able to do what we call sub-carrier selective, 

multi-carrier CDMA – in other words, it sculpts itself into a 

different shape, to fit around the existing user. We see lots of 

examples of this kind of work. The main point to take from 

here is that a lot of software radio research that we see in the 

world today has come up with a great many different ways of 

making every single parameter of a radio a variable that can 

be set as desired and when desired. 

The other point is that there are better ways being developed all the time in the brain section of the radio. With all these 

parameters that can be set, there needs to be means of deciding how they should be set and this is where the brain of 

the cognitive radio comes in. 

On this slide I have referenced a piece of research by Tom Rondeau. Tom designed a cognitive engine based around 

genetic algorithms and case based reasoning, in order to be what he called ‘multi-objective’ optimisation. In other words 

his radio makes decisions on its performance characteristics using multi-objective optimisation. 




Essentially, he built the brain of the radio. He uses a genetic 

algorithm approach to come up with the appropriate answer 

and sculpt the signal in a shape that suits constraints of the 

environment. This is just one example of the kind of work 

that people are doing on the brain of the radio. 

The brain of a radio can be used in many different ways. 

Not only can you use the brain of the radio to make decisions 

as to how you set your parameters in your radio and sculpt 

and shape the signal, but you can also employ it to get the 

best use out of your given hardware. This suggests that, if 

you want to deal with reality, reality is full of mess. If you look 

at what happens when a signal goes into a receiver in a nonlinear 

region, and a whole load of inter-modulation distortion 

occurs, then by carefully selecting what band you choose to 

operate in, you can actually reduce this effect. This is work 

done by Preston Marshall and it suggests that you can use 

radios with far less good parameters of operation, and get 

away with using a kind of cheaper radio by being more careful about how you select the way it operates. 

There are all sorts of other developments which add to the hope for the future. This slides shows some nice work on 

reconfigurable antennas. This antenna very graphically captures the whole idea. This is a simple idea, like a coil which 

you can tighten and, by physically changing the shape, you can change the frequency that it works at. This can work in 

2.2 to 15GHz, by just changing the shape like that. 

The point to be made from these displays, for examples, is that you can pull and twist and shake and pull that signal 

from a spatial and temporal and frequency point of view much more effectively than you could before. I haven’t even 

begun to talk about the whole kind of MIMO and all the other antenna techniques that you could begin to bring into 

play in this kind of space. 

Rather than thinking of a licence, where you can transmit power at a maximum transmit power, people think much 

more from a ‘mask’ perspective. You think of using these various techniques to shape the signal, to fit within a defined 

mask. There are some interesting examples of how masks 

are defined in one of the Ofcom reports that I have 

mentioned here but, when you see it in terms of the 

technology that I just mentioned, you can now begin to 

think of masks as being something very dynamic that 

changes. This is not statically defined but it is defined in a 

way that is relative to the parameters around it. 

Sometimes, what has happened in spectrum management 

in the past is that most people – and probably there are a 

large number of exceptions in this room – but most 

people only think in terms of the technology that we 

currently have. I do not want to suggest that by talking 

about the technology that we currently have, that we 

should think about the future only in terms of those 

technologies. I would suggest that the way technology is 

evolving, and the way this level of reconfigurability and 

pushing, pulling and shaping of the signal is going, should 

allow us to free up our thinking, not compared with the 

node technologies per se, but think about the mask that 

you will create and how that mask is more dynamic and 

flexible. 


Of course, it is not just one mask, but you are talking about a network here, collectively – the nodes of the network, 

creating a mask that is co-existing with something next to it. This is the way that we need to think, more from a 

network perspective rather than an individual perspective. By this, I do not mean a network perspective as my network, 

or the Vodafone network, or a different network with their nodes, but I mean it in terms of neighbouring networks. 

You have seen much work in the area of cognitive networks, 

where it is not just about making a decision at the individual 

node level, but it is making a decision at what they call a 

multilateral level, where all sorts of nodes have to interact 

with each other and come to a distributed but agreed 

answer or decision. If you think of this as a multiple network, 

starting with that cube diagram, co-existing next to each 

other and having some small level of collaboration, you can 

begin to think how perhaps these more dynamic masks, more dynamic standards, come into being. 

Another way to think of this dynamism, going back to the blocks again, if spectrum users, co-existing side by side with 

each other, these spectrum users can begin dynamically to introduce self-imposed guidelines. In this you are saying, if I 

am using this spectrum and I use a certain kind of technology – very advanced technology that can be close to the 

signal, and I can most efficiently use the spectrum I want, I might only have to have a small guard bands, whereas if I sit 

in this space and I want to use older, more static technology, then I can have big guard bands and I can discard them 

without caution and I am willing to give up my spectrum 

efficiency for that. So again, you are taking away the 

decision from on high and you are pushing it down to the 

people who are actually deciding on what technology to use. 

You can go further than that, and this is where the notion of 

bargaining begins to come in. You can think about entities 

that co-exist or are neighbours, bargaining with each other. 

Obviously, there are payments and various different things 

that come into play with this. For example, if these two 

neighbours do not co-operate and this one has to use a big 

chunk of guard bands and that one uses a small amount of 

guard bands, there could be some way to allow bargaining 

to happen. So it allows this person or entity to encroach on 

your spectrum but overall it will increase the usable 

spectrum and obviously, entity B needs some kind of reward 

for you allowing them to approach their spectrum which, over time, will be hard cash. 

When I first looked at this, I wondered whether this was an unreasonable level of negotiation and collaboration or coordination 

to expect between two potentially hugely competing entities, that are side by side. However, when I 

stepped back, if you think now about the way, for example, a lot of mobile companies share the tower structures for 

their base stations, and technology now, it is just as well that different companies can actually share the base stations if 

they so choose. I am sure that the decline in that level of sharing would not have been envisaged – it would be 

contrary to the way that people think about how you would do business with a competitor. Thinking in this kind of 

neighbouring, collaborative and co-ordinating way, where bargaining might happen, after you set up an initial base 

system, is not beyond the realistic way of thinking. 

To summarise all of that and put it into context we can look at the next few slides. In In this slide a target economic 

service area is depicted. You then specify the technology you will use and do some spectrum planning and you decide 

that, the package of spectrum rights you want will need to be a little bigger than the target economic area allowing for 

the effects of the technology. If you use smart smart sensing and sculpting of technology you may not need to buy 

that much in excess of the target area but if you use more limited technologies you may want to err of the side of 

caution. So the choice is the spectrum consumers. So it is a different perspective but certainly the kinds of technology 

that we have and that we can see emerging are contributing to making this kind of approach more realistic. 




There is an enormous amount of computing required in many of these things. There can be extremely complicated 

reasoning and analysis to be done to take in a whole load of information to process that and make decisions. However 

the ability to do this kind of comuputataion is more widely available. 

I have a small example here, of the spectrum correlation 

Useable Bandwith 

function. Essentially, if you want to detect the presence of a 

signal for example, you can use an energy detector – but an 

energy detector may not be good for signals with low power, 

like a spread spectrum, but people sometimes use what they 

call cyclo-stationary analysis to detect the presence of a very 

Useable Bandwith 

low powered signal. Signal inherently have cyclo-stationary 

features in them which occur as a by product of the natural 

processing of the signal (e.g. modulation of the signal). 

The cyclo-stationary feature detector allows you, having some 

knowledge of the signal in advance, to look for these features. 

If you try to do this on a general purpose processor, for 

software radio currently, it can be quite difficult, because the processing involved is extremely complicated and the GPP 

cannot handle the processing fast enough. 

What comes to the rescue is the Playstation 3 and you will see that, more and more now, people are using the Cell BE to 

do all sorts of interesting things. The Cell BE can do real time cyclostationary processing with ease – the video here 

capture the output of the process and was recorded in my lab. [Video not shown] 

Essentially, you can do a spectral correlation function – a live spectral correlation function – just using the Playstation 3. 

It can take an 8 MHz signal and do a real time spectral correlation function. The only reason I am showing that is 

because it is indicative of what can be done when it comes to processing data, and the really high, super-duper 

processing that exists. When we started our research into cognitive radio function, it was really hard to do an FM 

receiver on a PC, whereas now we can do all sorts of incredibly complex things. Playstation 3 has 6 SPEs in it but you 

can get larger numbers in other systems. The Playstation 3 is only about $400. It just goes to show that the price 

ranges are changing and that complex processing needed for the brain of a cognitive radio is more and more possible. 

There are very exciting advances in the design of heterogeneous fabrics on which signal processing can be done. 

The focus is the world is very much on parallel processing, and that is what happens in the Cell BE, as I mentioned. 

You do not need to think just in terms of arrays of homogenous processors but you can actually think of things in terms 

of arrays of heterogeneous processors. It will be possible to map different processing challenges to different processing 

elements in your heterogeneous array of processors. 

So when you talk about reconfigurability, you are actually talking about a lot of different things now. You are talking 

about reconfiguring your signal, shaping and sculpting your signal, and changing your waveform. You are talking about 

reconfigurability at the MAC layer and reconfigurability at network layer. You are also talking about reconfigurability of 

the resources you use. Sometimes, it might be more appropriate to use an FPGA, a mixture of DSP, or a mixture of GPP 

or whatever. More and more, you see high level design that allows you to direct your resources to where and when it is 

needed. This underlies the fact that much of what we are talking about here is more and more possible as time goes 

on. 

As I said at the beginning of this section, there are so many different areas that contribute to filling out the picture of 

how this world is emerging and what is happening. What I have here is a screen chart of a policy-based management 

approach to radio. This allows you to instruct the radio about how to behave in quite a dynamic fashion. You could 

have a regulator who sets policies in some kind of centralised fashion, and those policies would filter out to the radios, 

which in real time would implement that. They could download new policies as they move to new jurisdictions, and 

the policies can also be hierarchical and dynamic. You see more of this policy-based management filtering through 

much of the radio work that you see today. Again, you are adding to this whole picture, and not only do you have 

reconfigurable entities that sculpt and shape and make best use of resources, you have ways of instructing and 

managing those radios that weren’t so dynamic when they existed before. 


I apologise for hopping between topics in this section, but this is the reality of this type of area. That is why we now 

hop to combinatorial auctions. Auctions come in to play when dealing with spectrum trading. There is some very 

interesting work in combinatorial options that can support the fluid spectrum management concepts I have been 

referring to throughout the talk. 

Rather than saying, ‘I am putting in a bid for this one chunk of spectrum’, you can use a combinatorial option say that 

you want to bid for this chunk or that chunk, but you can even make that bid more expressive and you can say, ‘I would 

like any piece of spectrum here, or I would like it there, or I want it anywhere along there.’ – these kinds of expressions. 

This is becoming a much more key topic of research and essentially the whole point here is that the more expressive 

you allow the auction to be, the more efficiently you can help fill in the pattern you want to develop. So, on one side, 

we have the technology advances and on the other side we have the kinds of ouction mechanisms that you can 

imagine tie into those Rubik’s cube diagrams that existed in the first place - certainly at the initial stages and if not, there 

are other options that are being signed up to in spectrum-type approaches. 

CRFS 

When you think of this kind of spectrum world view, you will have to think differently, first of all about how it is policed, 

but you also need to think differently about any entities needing information to make the kinds of decisions we have to 

make. This leads you to think differently about different business models. There are opportunities for companies who 

do spectrum monitoring and provide usage databases, in this case for spectrum monitoring systems, that actually feed 

in as a live service into radios, to use that information to make decisions. It makes you think in a different way about 

how a mobile or radio communications entity can be divided up. I told Dave Cleevely I would include a picture of his 

company! These kinds of companies feed into the reality of being more liable. 

Continuing the move from topic to topic we now move on to another challenge. In a very dynamic world radios need 

to be able to find each other without knowing in advances the frequencies at which they will operate. Just in time 

spectrum users may fall into this category as well as dynamic spectrum access users. 

One technique you can that can be used to let another communication device know the frequency you are using, 

without the need for a control channel is a cyclo-stationary signature. As I mentioned earlier, many signals have 

inherent periodicities in them and those inherent periodicities are sometimes useful in helping you to find or identify 

that that signal is present. What you do with a cyclo-stationary signature is you intentionally embed a signature in the 

signal and, in this particular case, you intentionally embed it as an OFDM signal by correlating various sub-carriers, and 

you get something like this shown on the slide. This enables automatic frequency acquisition, because the signature 

tells you something about the frequency of operation of the transmitting device and it also tells you something about 

the identity of that network. This signature is like some kind of digital watermark that can be found by other users. 

You can obviously make the signature more complex in order to make it robust to multipath environments where you 

might have frequency selected fading. It can be combined with MIMO. In this case one antenna fist transmits the 

signature and later the second antenna transmits the signature – this happens repeatedly – and we get a diversity gain. 

That is the whole beauty of this reconfigurable world, where you can build blocks and you can combine them together, 

and see what kind of gains you get from them. I had a little video, showing one of these systems working in reality, but 

I will not try to run that now. 

The upshot of all of this is that, again, there is an enormous number of devices and a whole world of reconfigurable 

systems that allows you to think about this much more fluid way of allocating spectrum. 

CTVR bands 

More and more around the world, we also see now the opportunity to experiment with real-life spectrum. In Ireland in 

particular, they have a whole range of test licence schemes and my research goes back to what happens to be the 

frequencies we own for our testing of various ideas that we have. In Japan, they talk about the ubiquitous zones of 

deregulation and in various other countries, such as Singapore, there are areas where you can go and test. And while in 

itself this is not some kind of technological advance, it is yet another factor which contributes to the broader picture of 

allowing experiments with real spectrum, with real equipment that can explore whether these ideas can work. 




I thought it would be safe to leave you with a quotation from a very well-known person who has a huge amount of 

experience in the field of communication – Simon Haykin. He put this extremely well. He wasn’t talking about fluid 

spectrum markets, but he said: 

“I see the emergence of a new discipline called Cognitive Dynamic Systems, which builds on ideas in statistical signal 

processing, stochastic control, and information theory, and weaves those well-developed ideas into new ones drawn 

from neuroscience, statistical learning theory, and game theory. The discipline will provide principled tools for the 

design and development of a new generation of wireless dynamic systems exemplified by cognitive radio and 

cognitive radar with efficiency, effectiveness, and robustness as to the hallmarks of performance.” 

I think that is a very hopeful, forward-looking comment which says that we have all these technologies and tools that 

we can put to good use. One of my suggestions for good use is to move towards a very fluid way of managing and 

using spectrum. This hopefully, will not result in chaos and we may gain huge efficiencies by moving to the edge of it. 

So we can either think that we have a skeleton, with everything we need. 

Or you might think the skeleton looks more like this. Undoubtedly, however, I think we are on the way there. 

My conclusion is that we are beginning to have the technologies that can bring us to the edge of chaos and I think that 

trading in fresh air is probably far more solid than trading in the stock markets these days! [Applause] 



Michael Walker: Now is the time for everyone to participate in the question session. Our speaker has agreed that she 

is happy to take questions and the floor is open. 

Mr Jim Munro (Intellect): That was a very interesting talk. The party line from very senior researchers at Ofcom and 

elsewhere has been that cognitive radio is still over the horizon. You seem to be painting a somewhat different picture. 

How would you reconcile these two viewpoints? 

Linda Doyle: First, I am certainly not saying that cognitive radio will be here tomorrow. Secondly, the definition of 

cognitive radio is widely varied and there are some people who talk about the all-singing, all-dancing, everythingunder-the-sun 

cognitive radio. It is easy to say that that is still some way away. 

However, Ofcom themselves to a certain extent are contradictory because their press statement about the interleaved 

spaces on the TV bands was very supportive of the idea of supporting devices that would do no harm there, and that 

included cognitive devices. What I have seen in Ofcom itself is a change – although I do not know the senior people in 

Ofcom perhaps as you do – from ‘it’s miles and miles away’, to ‘it’s actually nearer than we think’. That is MIMO’s 

evidence, that they are beginning to take a slightly nearer term view of where it goes. 

Mr Brian Levy (Hewlett Packard Ltd): Dr Doyle, that was a very interesting talk but you did not mention a few things. 

Propagation: you indicated, or tended to indicate, that all frequencies were the same, with very different propagation at 

different frequencies, linked budgets and all those things. You talked about signal morphing and that that affects 

spectral efficiency. Then there is the linkage to applications, because applications require certain bit rates, certain 

parameters. How, in the chaos world, can we deal with all of that? 

Linda Doyle: You are very true in saying that not all spectrum is equal and it is the case that, when you present some 

of these ideas, and certainly when you draw them in the way that I do, this comes across. You will often hear the term 

‘beach fun property’, when they talk about certain spectrum being more desirable than others. 

I agree 100 per cent with what you say but I look at this in two ways. You are not dictating what people should use 

which frequencies for. Certainly, users of certain services and certain kinds of applications will cluster around certain 

frequencies. The economist’s viewpoint is that if everyone wants the same frequencies, then the people who put the 

greatest value on them and are willing to pay the most should then have them. That is secondary, I suppose, to what 

you are asking. It is not the case that I am saying that anything can be used for anything under the sun; I am saying 

what is most appropriate and what is driven by the market, and what the consumer of that spectrum chooses to use, is 

up to them, while acknowledging the fact that not everything is necessarily suitable for everything, and of course it is 

not because you sometimes want really long coverage areas. Sometimes you want the complete opposite and you 

don’t want your signal to go very far. There are all sorts of other issues that you need to take into account. 

I agree with what you say, but that is and can be part of the picture. 

Professor Ralph Benjamin (Bristol University): You talked of monitoring spectral occupancy and responding to it 

adaptively but, in fact, as you rightly recognised, you are really concerned not with spectrum but with transmission 

capacity, which is multi-dimensional, frequency, time, space and in fact the fourth dimension, modulation pattern. 

It is that total space that you want to use in the best way. 

If you use dynamic spectrum allocation, based on some form of marketing or bidding, then you need a cost function. 

Cost function cannot just be commercial cost, because there are also such things as social value and social need and 

you have to find a way of combining those in the bidding process. 

When you use software reconfigured radios, at the same time you have to reconfigure or adapt the user’s mode of 

operation to the changing cost of capacity. If you have achieved all of this, it means that there is all the mechanism and 

incentive to exploit gaps and to equalise the use of capacity in frequency, time and space overall. Therefore, the only 




way you can react to increasing demand is by increasing complexity or possibly by increasing power – but, hopefully, by 

increasing complexity because power poses more interference in any case. Thank you. 

Linda Doyle: You make some very sensible and wise comments. It is the case that you are increasing complexity with 

all of these things and that is the trade-off that you make. With the systems we have, the underlying processing 

capabilities are much more able to deal with them now. Even though the power you expend in all of these things is still 

greater than in simpler, more straightforward systems, it is greatly reducing. If you look at the power expended in some 

of the more parallel processing environments, it is an improvement over the kind of soft radios that people have been 

using up to now. 

You also talk about social needs, which many people mention when you talk about any kind of very fluid markets. 

This is a very important point. I actually support Ofcom’s approach to that myself. My understanding of their approach 

– and if anyone here has a different understanding, please chip in – is that you pay for spectrum and you pay what the 

value of that spectrum is. If there is a social need to be addressed, you get funding in order to help you to buy it, but 

you do not actually give it away free. That is probably a very blunt paraphrasing of the policies here. 

I have heard somebody say that if, for example, you think that there is a social need to build a cinema in, say, a very 

remote area, but you argue that there is not an economic need, you give people grants to build it – but you do not give 

them the materials free. I support that kind of mindset but you are right to say that there is also the public safety 

spectrum. 

I made the point earlier that you can start from where we are now. The reality is that we will have quite a patchwork 

future, with different regimes in different spaces. You could still imagine an administrative approach having to exist in 

certain areas. I am sure that there will be some cases for military use and so on, but certainly striving for this more fluid 

approach opens up more opportunities than it closes. 

Mr Stephen Temple: I was in the old world of spectrum management for about 20 years and more recently I have 

spent a couple of years on the Ofcom Spectrum Advisory Group when they went through their thinking on spectrum 

auctions. 

Rather than a question, I have more of a comment for you to react to. You started with the political context and then 

you moved down into the technology. I would not question the technology part because it sounded very interesting, 

but I wanted to comment on the political context. With the administrative approach, you referred to it being 

unresponsive, with people sitting in ivory towers, dictating what should happen, and they made mistakes from time to 

time. I would actually want to blow those myths away. 

First, if you go back to the days of Marconi, 113 years ago, the history has been consistent of a technology coming along 

and a market need, and then the government having to respond to it. It has been a reactive process, rather than people 

sitting there and having their own ideas. If you look at those 113 years, they got enough things right – it is not that they 

got everything right, but they got enough things right. I would look at any private sector company, and the test is 

whether they get enough things right. I do not know of an industrial company in the world that has got everything 

right. Mike is in R&D and if he achieved a 20 per cent hit rate he would think he was doing very well. The private sector 

gets it wrong 80 per cent of the time. 

If you look back at the history of radio and spectrum allocation, they actually did a brilliant job. They got all the space 

spectrum done in time, and GSM was done in time and so on. They got enough things right, although a few things 

were wrong – short-range radio, Irmies, to think of two examples. I want to blow the myth away that the government 

has made a mistake and therefore it is the wrong way of doing it, because the private sector would make as many 

mistakes, if not more. 

The second myth is this idea of the ivory towers. If you look, you would be reacting to pressures. All the time in 

government, people are coming along – industrialists and commercial people – so I think that was not quite right. 

The third one, which is the biggest myth of all, is about this discontent with the administrative system. I was in the 

industry by the time all these changes occurred and no one within the industry was calling for spectrum auctions. 


Nobody – believe you me, it came out of the Treasury, which thought it was a great idea, and economists thought it 

was a great idea. They were all people out of the industry, who knew nothing about the industry, that spread the socalled 

discontent. People were actually very happy within the industry. 

I then look at the model you are creating and, in a sense, you slightly backed off from the first part, when you said that 

this would have a space and it would be administered alongside, and that is the way I think it should be. However, if 

you say that this should sweep the old world away, then I would characterise your new world as sweeping out the 

prudent old world, unfettered market forces will deliver superior performance, and you create a system so complex that 

no one understands it. Now, those three things have just described the banking deregulation. [Laughter] In a sense, 

that is what you are trying to bring across as the new world. 

I have sat on certain advisory groups and I actually think that Ofcom are on the wrong track with spectrum trading. 

I think it will end in tears, although I will not spend the next half hour explaining why. They have not understood, for 

example, about the important role of spectrum re-farming. If you look at GSM spectrum, for example, that has been 

re-farmed three times. As soon as you have unfettered market forces fragmented, suddenly that way of regenerating 

spectrum is lost and gone for ever. Technology neutrality is the biggest value destruction possible - for someone trying 

to sell off spectrum, it has to be technologically neutral. 

Not aligning with Europe is a total disaster. If you take the Rubik’s cube, and if you have to get the Rubik’s cubes of 25 

member states all to line up within a European-wide service, it will not happen with unfettered market forces. You can 

go on and on and on – it is a flawed approach. 

That said, I think your technologic approach is good. It has its place and its role and should have its space. 

The regulator should find spectrum for it in order for it to contribute to the economy. This is less of a question and 

more of a provocation, and you are free to react to it. 

Linda Doyle: Your comments are very interesting and well made. When you are presenting an idea and giving a talk in 

the time available, you cannot convey all the nuances. Some of my comments may have sounded blunt in the sense in 

that they were probably too quick a way of saying it. 

Referring to people in ivory towers making decisions, I was emphasising the fact that the centralised decision is distinct 

from a distributed decision and there was no insult to individuals or groups intended. 

You mentioned auctions. There was a lot of happiness on one side with auctions, that revenue was generated, and 

there was also a lot of unhappiness among operators who had to spend an enormous amount of money. There were a 

number of extremely serious implications. However, I’m not arguing for auctions per se but I am arguing for a freer and 

fluid situation and all of the auctions that I have seen take place are falsely fluid in the sense that, around them, they 

have this tightly regulated system, and they have taken one thing from that and freed it up. 

They have then said that this is like a free system, which can go whichever way it wants and the market can drive it, but 

it has all these other anchor points, if you know what I mean. You are half doing something, and looking at that and 

saying that it does not succeed is not looking at what the picture could really be – it is looking at a half-implementation 

of it. Any time you begin to see things freeing up, even like in the 700 MHz auctions in the US or even in some of the 

Ofcom auctions where they are more flexible and you could do combination things, you are still surrounded by a 

structure that it is fitting into. I think there is more potential in these ideas but I also think it is very difficult, starting from 

the system we have. 

I used the word ‘Utopia’ specifically when I gave that description to describe what it would look like if we were all like 

that. It is not a backing away on my part to say that it will not fully be like that – it is an acceptance of reality. 

I specifically boxed that thing with the Utopian view, but I still believe in the merit of much of what is in there. There is 

a wider space than you think for it. 

Unfortunately, I did not attend a talk at which Vivien Reading was speaking in Ireland. From what she said, it sounds 

very much like the whole notion of a European regulator. When she was talking about the ‘digital dividend’, she was 




referring to this 50:50 notion, where broadcasters would have 50 per cent dividend from the digital dividend and 50 per 

cent would go to the wider public. Once again, there was great emphasis on harmonisation, which has given 

enormous benefit. However, I have to say that I cannot agree with that tightening down of things that she is 

suggesting, or the fact that everything has to be harmonised in this way. There is space for this, although the issues you 

mentioned are very real. I do not mean that as a cop-out, because it is the reality. 

Dr David Cleevely (CRFS Ltd): I am on the Ofcom Spectrum Advisory Board and I was wondering whether I have 

perhaps spent a little too much time with Stephen because my question is very similar to his in its fundamentals, 

although it is a little more theoretical than that. It is about your point on the edge of chaos and the complexity which 

you are advocating. 

To reach any optima, you have to have a search space or a cost function, or whatever we are referring to, that is 

reasonably smooth and continuous. I am not clear that your Rubik’s cube satisfies any of those conditions. It looks like a 

highly serrated landscape to me. When you look at the combinatorial auctions, the amount of chuntering through of 

calculations that you need to do - simply because actually searching that space is very difficult - is an indicator of 

something perhaps a little worrying. It is not only that it is rather difficult to find where the optima might lie but, 

secondly, the system itself might actually exhibit some pretty pathological behaviours. That is where we link to the 

banking system because we can see for ourselves a truly pathological behaviour that this developed, as a result of 

precisely – precisely – that inherent property of the system. 

What is your gut feeling about this? Otherwise, Viviane Reding’s 50:50 is actually quite a good, pragmatic approach. 

If you tie the system down enough, so that it can’t wander off in some state space fashion, into some really nasty state, 

then perhaps that is a better way of handling things. 

Linda Doyle: Here, I am not talking about no regulation, for a start - I just want to clear that up - but it is the light touch 

of regulation that I am advocating. In the last week, I admit that I have been thinking that this is a very strange time to 

be advocating the kind of things I am, given everything that has happened in the world. The banking system, as you 

point out, is a very good example of that. However, the banking system is also an example of being completely 

unregulated, with no rules, and people turning a blind eye and not policing it, and not checking up on the rules that did 

exist. In that sense, it is also an unfair comparison. 

My gut reaction is that I agree with you, that there need to be anchor points. Things need to be tied down, or things 

need to be eliminated. I believe that the best way to do that is to push out the boundaries in imagining, and then pull 

them back in, rather than going the other way – and, for me, the system goes the other way. It starts with all the good 

things and the flaws and it incrementally tries to think out from there, and that is why I think we should go the other 

way. 

I do not think you will get out to the edge of chaos, if you want to accept that as a scientific term of where it is. I do not 

think you will get near there, but you need to think about being there and come back in. 

Matthew Postgate (BBC): I have a comment and a question – perhaps a softer question than some of the 

engineering-focused ones. 

I thought your talk was fascinating and I really support these kinds of ideas. We have a long way to go, but perhaps we 

are closer than we may have realised. Having the privilege of working for the BBC means that I work with arts 

graduates and science graduates, across that particular spectrum. Having had that experience, my observation is that 

where you promote competition at one end of the value chain, you tend to restrict it somewhere else. Some people 

feel that multiple distribution technologies are a good thing but, if you are there trying to create editorial propositions 

on multiple systems, you end up with lowest common denominator approaches which are suboptimal, and vice versa 

with reality issues. Coming from the research institute that you do, this might be something you have already 

considered. 


The second aspect of my comment is that, when we made the transition with Ofcom from the very ‘command and 

control’ approach to the ‘let the market decide’ approach, my understanding from the presentation that I attended 

about that was that there was a third way. The one thing that has not happened is that there has not been any more 

unlicensed spectrum, but I think there is a role for that as well. I am not sure where that ended up – in the bin, 

probably. 

My question is that, if the future should pan out – and hopefully soon – in the way that you have described, I would say 

that in terms of the social ends of these technologies, what I have learned at the BBC is that there are often many 

different ways to skin a cat. Society, for whatever reason, no longer feels that it is capable of delivering cathedrals that 

take 200 years to build and yet we still provide social ends associated with those kinds of constructs. What would 

happen in this world to the actual applications, that people might actually use? Are there any trends? Is it a trend away 

from broadcasting to more point-to-point applications? Is it a trend towards social applications or broadcast 

applications? I am interested in your views on that. 

Linda Doyle: You have made a range of very interesting comments. Starting with your last point, there is a trend away 

from broadcasting as we know it anyway, and I think everyone sees that. The whole idea of you having an entity that 

radiates out a signal, and a thing that just receives – those days are gone, in the sense that everything is a two-way 

thing now. I have to say that I completely object to the term ‘broadcast spectrum’, because spectrum is spectrum, and 

labelling it in an ownership way like that would go against my views of that. 

How general applications will go – I have to say that there is a whole variety of things. There is more disruption tolerant 

networking ideas, and all the social networking. However, I am not the best person to pick the applications and this is 

what this is saying – that you do not have to pick them in advance. 

You mentioned the licence-exempt approaches and it is very true that that is the way of going about things. A number 

of the things I spoke about could be implemented, like the dynamic spectrum access, for example, at the beginning. 

There are models where you can have dynamic spectrum access in an unlicensed way and some of the technologies 

that are being suggested for the TV – the interleaved spectrum, the TV white spaces – would be an unlicensed 

approached, but there are licensed approaches that you can take to it as well. 

In terms of general, common type approaches, Ofcom – according to their figures – say that there is really very little 

need to increase the amount of spectrum hugely that is devoted to that. There might be other people who would 

disagree with that approach and think that it should be completely freed up but the figures that they would report on 

the basis of research and evidence that they have show that there is only about six per cent of the spectrum here in the 

common space, and that will only grow to seven per cent in the future. That is the kind of demand that they foresee. 

They have some very interesting work on suggestions for licensing frameworks, in which you take different approaches 

to having different kinds of these regions, with different applications working under different rules and different 

etiquettes as they call it. 

Professor Jonathan Chambers (Loughborough University): My question is technology orientated. You mentioned 

briefly about interference and that will be a major issue in terms of dynamic spectrum allocation. There is much 

concern about the so-called ‘hidden terminal’ problem. Could you offer a little more insight into where you feel 

solutions might come from, in terms of handling such interference? 

Linda Doyle: The common belief, with regard to dynamic spectrum access and hidden terminal is that you need to 

collaborate, so nodes in a network have to collaborate in some way in order to overcome the interference. There is 

interesting research in collaboration on sensing and the fusing of information, and the sharing of that information. 

That seems to be a sensible way to progress in that. 

There are challenges, too, in the sense that to have the right level of collaboration, you need the right distribution of 

devices, but I do not think I expressed this very well earlier. I put up the slide about spectrum monitoring, but there are 

also people who are also thinking in external services that exist, and those external services would provide information 




that you might get free, that you might buy, or that you might interact with in some other way. That information would 

be gathered from the proper kind of distribution of devices or entities, but then it would feed into your system and 

allow you to make those sensible decisions. 

If you look at some of the techniques people are considering, this is where learning comes into play a good deal. 

You can take approaches that mean that, when you go to transmit, you can observe patterns and behaviours that make 

you transmit more successfully, without causing interference. There is a whole plethora of techniques that are 

happening on the technical side and there are different ways of thinking of services you might avail yourself of on the 

business side that could help with that kind of problem. 

Professor Raymond Steele: I thought your talk was excellent. I think you are looking ahead and so it is not fair to talk 

about cognitive radio if it is here tomorrow. It is some way away. 

Secondly, I think people will want to go out and buy or wear some form of transceiver which has all sorts of services. 

Let us say that it has some number that codes it, for what it is capable of doing. It is not interested in whether it is on 

the Vodafone network, the BBC network or any other network – it wants the service it requires, and it wants it delivered 

there and then. I am against spectral trading totally but I would like to say that the regulators need to change. I want to 

see software agents as regulators, not that I wish to get rid of all the human regulators – they can sit in their ivory tower, 

and come on the television and talk about things. However, when it comes to allocating spectrum, if we all wait for 

them to do it in your cognitive way, it would never happen, or it would take too long. 

I also do not believe that you can have bruisers, that two people or a number of networks start fighting each other. So I 

wish to put a regulator in and so I have this device. I know what service, so I hit a button indicating the service I want. 

It sends a signal out on a specific frequency and one of the radio stations is then mandated – like the Vodafone mast or 

whatever is available – to pick up this signal. It is like going to a website. It knows what is going on there. The message 

is extremely short: it says what you are capable of and what you want. It knows what everybody is doing and it tries to 

find you a slot, so it is a regulator. It does not allow chaos. 

It took about 100 years for the government to realise that you could get some money out of spectrum. I am waiting for 

them to tax breathing air – it is just a question of time. I want to go back to how it was. We did not need to get piles of 

money from it before and as for it being more efficiently used, I think that is highly disputable. When I think of your 

company, for example, sitting for ages on 6MHz or 10MHz spectrum which you had – and not just you, but everybody – 

for four years or more, this is just an absolute waste. 

Linda Doyle: I agree with that. 

Raymond Steele: Almost any system that I ever came across – any system, anywhere in the world – the utilisation on 

any base station is nowhere near 100 per cent and it is often as low as 10 per cent. It can be very, very low, even at busy 

times, and certain parts of the City just aren’t getting calls. We really want to have a software agent regulating it, and we 

want to allow this cognitive thing. The real brains is in the regulator but the actual software radios have to be able to 

get messages back and be told what to do. 

Linda Doyle: I can see that you are clearly against the idea of spectrum trading, but I would like to make a comment. 

I think I am using a much more general description of what trading is and your description of a software agent in the 

radio is a trading – so trading is a proxy thing. The way I think about it, you are slicing up a cake, but how do you decide 

how to slice it? 

Raymond Steele: The regulator is the boss. That software agent, sitting over there on that site, tells any user what it 

can do, where it can do it and when it can do it, or denies it. 

Linda Doyle: What you have actually described there is exactly how people describe brokers in spectrum trading 

entities. All the spectrum trading entities that you read about are not necessarily anything like I have described here 

but, for example, people talk about spectrum pooling where various different cellular operators decide to come 

together and pool the spectrum they have and re-trade it out. There is some kind of entity – a broker, or whatever you 


want to call it – that sits there and knows what can happen so chaos cannot ensue. When you put in your bid, it 

decides. The bid does not have to be money, but there is a mechanism by which you assign the resource. This can be 

some kind of proxy measure, or it can be hard cash, or it can be something else. 

I saw that E2R has a European programme on end-to-end reconfigurability and they had an interesting comment where 

companies came together, pooled spectrum. Everyone had a base amount and then they re-bid for the spectrum on 

an hourly basis or some time slot that they thought made sense. However, what actually happened was that there was 

some way then of redistributing the money that came in from that among those companies, or redistributing the costs 

or something. It does not always having to be trading in the sense – because the agents you describe – 

Raymond Steele: Obviously, the amount of various and spectrum and other things you use, you have to pay for. 

Linda Doyle: Anyway, I just think you are talking about spectrum trading in a different way. 

Raymond Steele: I want to bring back regulators and I want to get rid of people paying lots of money for spectrum, 

and bankrupting the industry. 

Linda Doyle: But the other side of that trading – as I said earlier, trading does not mean that people will spend the 

most horrible sums of money on spectrum. What actually could happen is the complete opposite, when there is a free 

flow of things. I know that I am envisaging the future but, if I have a piece of technology that can use this spectrum or 

that spectrum, then I can take either one of them, and I will not be over-obsessed about having this one rather than 

that one. I will have a different way, and it could be cheaper for me. It might not be cheaper for the person who can 

only use one bunch of spectrum and are completely stuck to it. You are pre-supposing that spectrum trading means 

that everything will be an outrageous price. 

Raymond Steele: Look, on any cell, in any country, there are thousands of calls being cleared down and starting up. 

You have to have somebody in control. It is just ridiculous that you are all negotiating to have that bit of the spectrum 

or this bit of the spectrum. It is not like that: somebody says, ‘You have that bit.’ 

Linda Doyle: That is true, and I am not saying that you don’t have someone in control either. Also, one of the things I 

said at the beginning is that you can easily have very confused conversations about this, if everyone starts mixing 

timespans. You can talk about long-term spectrum trading, where people have large chunks of stability with spectrum 

over a larger amount of time, and lots of economists, if they see that cubic diagram, start asking why each of those 

blocks is not 10 years long. With the scale you are talking about, with those agents in it, you might be talking really 

short-term or you might be talking longer term, but it is a kind of spectrum trading. 

Mr Pike: I have a fear that, in the long term, these approaches of innovation run the risk of becoming a barrier to 

innovation. All of the techniques that have been described rely on co-operation in various ways. If they became 

ubiquitous across the radio spectrum space, then that would prevent any future innovations which could not cooperate 

for any reason, or would limit the functionality or performance to the degree of co-operation that exists in the 

incumbent systems. In fact, this approach actually sows the seeds of the same problems as it is trying to solve in the 

regulated regime but, if it comes across the whole spectrum space, there is not the way out for innovation that there is 

at the moment with different frequency bands. 

Linda Doyle: I see your point. The way I look at the interference issue and the shaping and sculpting of your mask is 

that there is a basic level. You create your mask and you stay within your mask, and you are fulfilling the conditions as 

required. You can improve your performance if negotiation and co-ordination happens, but it does not have to happen. 

However, as I pointed out, it is the case that you have certain levels of co-ordination and co-operation in the use of 

structural equipment currently and so that mindset already exists to some extent, and I do not see us stifling it in the 

sense you described, because it is not a necessity but it is something that would give you an extra benefit. I realise that 

something that could give you an extra benefit then becomes a necessity or could be in danger of doing so. I also think 

that you are leaving parameters open in many ways because you are not saying how this has to happen or what it 

actually means, but you leave a great deal of choice in the individual entity still. That is your safeguard against your 

fears. 




Mr Pike: If I could just respond to that, I think we already have a case in UWB that does not fit into your model of the 

Rubik’s cube. That is designed to co-exist but there might be things in the future – you are talking about parameters as 

a closed set and that is a difficulty with it. As long as you rely on a closed set, anything that does not fit in that closed 

set is precluded in the future. 

Linda Doyle: I had not intended the parameters to sound like a closed set, and this is the point that is very difficult in 

everything. It is hard to discuss things without thinking in terms of the technology we currently understand. Some of 

the problems we have had in the past have been on that exact basis. I would end by saying that this is something that 

I and others, if we go down this route, have to make sure that we do not do. It is a good point to be wary of. 

Michael Walker: I would never have believed that a lecture on spectrum on a Friday evening would have generated so 

many questions and so much emotion. Thank you very much for that, Linda. That proves it was a very splendid lecture. 

Let me also thank the audience for their participation. [Applause] 


From plain old Telephony to 

flawless mobile audio 

communication 

Wednesday, 4 February 2009 

Speaker: 

Prof Dr Ing Peter Vary 

Institute of Communication Systems and Data Processing 

Chair: 

Professor Michael Walker, FREng 




Michael Walker: Good evening, everybody, and welcome to the third lecture in the third of a series of lectures in 

mobile communications and networks, jointly hosted by the Royal Academy of Engineering and Vodafone. Before we 

start, let me introduce myself, because I am aware that there are a number of people in the audience whom I have not 

met. I am the Research and Development Director for the Vodafone Group and so I have a great interest in mobile 

communications and in telecommunications in general. 

It gives me great pleasure to introduce our speaker this evening: he is very well known in the mobile communications 

industry and he is Peter Vary from Aachen University. He got to Aachen by various routes. He was at Erlangen after he 

did his PhD and before that he was at Darmstadt. He then worked at Philips before going on the Aachen. Whilst he 

was at Philips, he led the team that invented the GSM codec, the voice codec, which is probably the most widely used 

voice codec ever invented. If you think of the number of people who now carry a GSM phone, which is getting on for 3 

billion, they are all using that codec. This was a tremendous piece of work. 

Since then, Peter has retained his interest in voice and in other aspects of digital signal processing. We really are very 

pleased that Peter has been able to accept the invitation to address us this evening. I will not say any more, other than 

that the title of his talk is From Plain Old Telephony to Flawless Mobile Audio Communications. Peter, could you address 

us. [Applause] 


From plain old Telephony to flawless 

mobile audio communication 

Professor Dr Ing Peter Vary 

Institute of Communication Systems and Data Processing, Germany 

First of all, I would like to say thank you: it is a great honour for me to give a talk here in the Royal Academy of 

Engineering, which I am very pleased to do. 

Speech communication is likely to remain the most important service in mobile communications and we may discuss 

that later, but that statement is not very exciting because our expectations are not too high. From experience, we know 

that a phone sounds like a phone, because it is a phone. We know, and it is obviously a matter of fact, that a mobile 

phone never sounds better than a fixed-line phone, because it is mobile, and it is wireless technology. In my talk, 

however, I will aim to convince you that this might not be true in the future, or even in the near future. 

The €1 mobile phone 

The state of the art phone is a very smart device. It is a telephone, a camera, an mp3 player, an FM radio, a calendar, a 

pocket calculator, a game box, and it is – or it seems to be – cheap, at just €1. The question is, is there still room for 

improvement? €1 is not too much. Our question should read: are there some improvements for which the customer is 

willing to pay more than €1? That might depend on the customer. 

To improve the phone, or to make it better, there are different criteria. One approach has been taken by the company, 

Vertu. This is an independent company belonging to Nokia and you can buy these nice phones: the price starts here at 

€20,000, rising to €30,000, €40,000 and €50,000. You can buy these in the shop at Frankfurt Airport, for example, where 

you buy Rolex watches. However, within the case, there is no Rolex or anything like that – it is just a plain Nokia phone. 

iPhone “Princess Plus” - €144,000 

Some people like to have more than just a plain phone – they like the iPhone. For those, there is also a solution by an 

Austrian designer. There is the Princess Plus at €144,000 but, inside, it is the same technology as a standard iPhone. 

iPhone 3G “Kings Button” - €1,790,000 

If that is not what you are looking for, because you would like 

to spend a little more, then this is probably the top iPhone 

you can buy at the moment. It has a lot of diamonds around 

the frame, and the central button is a very big diamond. 

Amazingly, the company does very well. It has 500 

employees – the company is Vertu – but the market is 

probably niche. [Laughter] There are a few clusters of 

customers in some regions of the world, as you can imagine. 

So this problem seems to have been solved and therefore I 

would like to address a different problem: to improve the 

phone not in terms of the outer appearance, but inside. 

I would like to discuss improving the audio quality. 


From old telephony to audio communication 

A phone sounds like a phone because it is a phone and the main reason for that is because we have a limited frequency 

bandwidth, which comes from the old days of the old analogue telephone. The upper frequency limit is 3.4 kHz, which 

was specified in the old days when we had analogue telephones and we had frequency division multiplex on the long 

range connections. This was kept when we switched to digital, and it was kept when we switched to GSM. This is the 

reason why the intelligibility of syllables is only 91 per cent, which is not too much. Therefore, on some occasions, we 

need to use a spelling alphabet to communicate a name or term that you have never heard before. 

The original speech might have frequencies up to 10 kHz or even more. The idea is to improve the quality by increasing 

the audio bandwidth, perhaps from 3.4 to 7 or even more. This raises new questions, and that is what I would like to 

discuss in this talk. 

Mobile audio-communication 

1.Technology evolution 

We have to discuss the technology in terms of the network, 

and in terms of the micro-electronics. We will then see what 

can be done as state of the art and in the near future to 

increase the audio bandwidth, such that we no longer need 

to make a distinction between speech and audio, and we 

increase the quality. If we have a better compression 

scheme, then the next question is, what is on the radio 

channel? We have a lot of interference and noise, but how 

can we protect and guarantee that, at the receiving end, we 

have the same excellent quality? 

Finally, I would like to share a vision with you – and that 

might be another topic for discussion. 

In the technology evolution in the network, there is the worldwide initiative NGMN on next generation mobile 

networks. This initiate was started by the leading network operators and the main goal is to increase - they are saying 

bandwidth, but it means bit rate - because this might be the driving force. The goals are very ambitious in terms of cost 

and performance, NGMN should be as close as possible to the digital subscriber line, the fixed network internet access. 

That is very ambitious but we, as engineers, like to have these ambitious goals. 

Evolution of data rates 

Let us look at DSL, which is a moving target because there are different versions. There is VDSL, for example with 

increasing data rates. We are presently somewhere here [on slide] and we can achieve reasonable data rates in the 

UMTS network – on the basic UMTS network, it is 384 kbits/s, but is depends how many users there are. If you study 

that more carefully, you can see that you can achieve 384 kbits/s, but perhaps five users at the same time because the 

data rate and the downlink is limited to 1.5 Mbits/s. However, there are efforts to increase it by HSPA (high speed packet 

access) in downlink and uplink and then you might really experience – and this is what my own experience is – that you 

will have 800 kbits/s or 1.2 Mbits/s and sometimes in the night perhaps even more in certain places. 

It was a decision of the NGMN initiative that their first solution would be the next generation of UMTS, which is called 

UMTS LTE. LTE stands for Long Term Evolution. The bit rate will be huge, and I do not know where the limit of this bar is 

but there is ongoing discussion about that. In any case, however, there will be plenty of bit rate. 

UMTS and GSM coverage in Germany – T-Mobile, Vodafone, 11/2007 

What is the actual status? Let us look at Germany. This map is public information with the status at November 2007, 

but it has not changed much since then. I have tried to give it neutral colours so that you cannot distinguish whether it 

is T-Mobile or Vodafone but, in any case, you can see that they are very similar. The green indicates UMTS and the grey is 

GSM, or the GPRS with packet radio, or the EDGE system, and the white dots indicate those happy places where you 

cannot use the phone at all. 


You can see that there is much room for improvement but, if 

you discuss it with the operators, they will tell you that that is 

already very expensive. For these green dots, the operators 

need 12,000 to 13,000 base stations already, and the 

coverage is 80 per cent of the population or even more. 

Perfect – but it is only 20% to 25% of the area and, if we 

compare that to GSM, for the grey area you need about 

18,000 to 19,000 base stations, so UMTS is much more 

expensive. This has to do with the UMTS frequency band but 

it also has to do with the transmission scheme, with the 

CDMA concept (Code Division Multiple Access). The sales are 

smaller and there is a big question mark about whether 

UMTS will ever be available everywhere. What we can 

conclude here is that we will see increasing data rates but 

there is limited coverage and, therefore, with GSM, there will be the fall-back solution for a very long time. If we try to 

improve the audio quality, then we should take care to see that we transport the quality in the GSM network. 

What about the implementation and complexity? Every time we invent a new codec or a new radio interface, 

complexity increases because we are making progress towards the theoretical limits. We are trying to improve the 

quality, so what about complexity? 

Global system for mobile communications 

Technology evolution: Moore’s law 

All the time it is the same. I would like to go back about 20 

years, when the GSM system was more or less stable and it 

was standardised. Experienced engineers in the company – 

I was with Philips – said that it would take 10 years or even 

longer until we would be able to implement it in mobile, 

because the GSM standard was so complex in comparison to 

the analogue FM radios that we had at that time, that the 

idea of the mobile should look like that. 

So much of the equipment is in the car and, to be honest, 

when we implemented the first test mobile station, it looked 

a little bit like that. This was in 1989. 

Just a few years later, in 1991/2, we had the first mobile, the 

Motorola International 3200. This was incredible progress in 

a couple of years. There are two reasons behind that. 

First, there is Moore’s law, which helps engineers to invent more complex things, and it says that the number of 

transistors on an integrated circuit has increased exponentially. The scale here is logarithmic, which means doubling 

approximately every two years. What does doubling mean? 

Implications of Moore’s law: 6 years later 

To get an idea, let’s take a chip of today and wait for six years. Six years is three times two, it is 2 to the power of 3, and 

that is a factor of eight. So we were able to reduce the chip size after six years, and we started the standardisation and 

then we entered the market and we were happy that the chips were becoming smaller and cheaper. On the other 

hand, if we have more space, we can also add additional functionality and new architectures. My conclusion for the 

voice service is that we should not worry too much about complexity, although that is a topic we could discuss. 

Mobile audio-communication 

Now let’s study the audio and speech compression schemes. In mobile radio, we use model-based speech coding, 


From plain old Telephony to flawless mobile audio communication 

which means that we have a technical model of the mechanism, how speech is produced. We have the vocal folds, that 

is the excitation generator; we have the vocal tract, which is an acoustic resonator, and we can map that to a digital 

solution; a source-filter model of speech with a signal generator, a digital generator, and a digital filter. We just need to 

extract from the speech the right parameters to control this model. 

Model-based speech transmission 

Model 

Parameter 

Extraction 

Coding & 

Modulation 

Vocal Tract 

Demodulat. 

& Decoding 

Tongue 

Signal 

Synthesis 

Generator 

Filter 

Parameter 

Speech 

Synthesis 

Therefore, in the mobile, we have A-to-D conversion, then 

we have model parameter extraction - the parameters of the 

vocal tract and the parameters of the excitation source – and 

we need some channel coding, error protection. Modulation, 

and synchronisation to transmit the parameters to the 

receiver at the other end. Where we have demodulation 

and decoding and error correction, we get the parameters 

and we re-synthesize the speech. What we are using there is 

a natural-sounding vocoder and this was the only solution 

because the bit rates are rather low. The sampling rate for 

telephone speech is 8 kHz and the bit rate is 8 kbits or 12 or 

less. If it is 8 kHz, we have 1 bit per sample on average, 

which is not too much. The secret is that it is adapted to the 

mechanism of speech – we model the mechanism of 

speech production and it is adapted to the mechanism of 

perception – the human ear. 

Speech quality/audio bandwidth categories 

We have different categories but, unfortunately, so far we are using only the first one, which is for plain old telephones, 

the narrowband speech. There are standards meanwhile for wide band coding, which is 7 kHz, or even super wideband 

coding, which is 14 kHz, and the reference is the full-band at 20 kHz, although I do not know who can detect tones 

beyond 16 kHz – but that is at least the definition. 

AMR speech codecs for GSM and UMTS 

The most interesting codecs we are using nowadays, besides the very old full rate codec which is in every mobile, the 

most interesting at the moment is what is called the adaptive multirate speech codec. This version that is presently in 

most of the latest mobiles is the AMR narrowband codec. It is still the old bandwidth but it has eight different bit rates 

from 4.75 to 12.2 kbits/s. For 12.2 kbits/s, the best mode is the same as what is called the enhanced full rate speech 

codec (EFR), which was there before. 

Then there is a different version – a different standard but 

with the same name – adaptive multirate wideband (AMR- 

WB), with a bandwidth of 7kHz. The sampling frequency 

then is 16 kHz and the 9 bit rates are between 6.6 and 23 or 

24 kbit/s. At 24 kbits, and sampling at 16 kHz, that is 1.5 bit 

on the average per sample, and 6.6 is a little more than ⅓ of 

a bit per sample. 

The concept is called code excited linear prediction (CELP), 

which is a sophisticated model of speech production. You 

see the vocal tract filter and two stages – although I will not 

go into detail because, to a certain extent, it is a model of the 

vocal folds mechanism and the acoustic vocal tract. We see 

there some excitation generator, which is a vector code book. 

From the transmitter, over the radio channel, we get the 

parameters: that is, the address from the vector code book. In the vector code book, we have short segments of 

samples – typically 40 samples. Let’s say that we have there 1,024 versions of 40 samples. We do not need to transmit 

40 samples because the transmitter and the receiver have the same code book and we just transmit the address. If it is 


1024, we transmit 10 bits, so to speak: we don’t transmit the joke, but we just transmit the number of the joke: we 

receive a notice of the joke and then we can decode it. Then we have the gain factor and the filter coefficients. 

We update the filter 50 times per second, and we update the excitation codebook 200 times per second. That is going 

on in the mobile. 

Adaptive multi-rate narrowband codec (AMR-NB) 

Let’s discuss the idea of adaptive multirate coding. There are two modes, the full-rate mode, and there is the half-rate 

mode. In the full-rate mode we have 22.8 kbit/s, in the full-rate channel and, for the AMR codec, we have a dynamic 

allocation of the bit rates to speech coding and error protection, depending on the instantaneous quality of the 

channel. Every 40 milliseconds, we can change the code and, if the channel gets bad, we should add more error 

protection while, if the channel is clear, we need less error protection. 

Let’s study the clear channel. We take the best version of the codec that we have, the 12.2 kbit/s version, the good 

channel, and we need some error protection. If a mobile is inside a building, the channel gets worse and we have 

additional attenuation – perhaps 20 dB attenuation, so we have a lot of errors. When we have a weak received signal, 

we add at the transmit site a lot of error protection and we reduce the bit-rate for speech coding. That changes 

dynamically. 

The objective of the AMR narrowband codec is to increase the robustness – I am saying here at the expense of the 

speech bit rate. What does that mean? If the bit rate is 12.2, then the speech quality at the transmitter is the best we 

can have: if the bit rate is only 4.75, however, then you really recognise some coding artefacts. In the end, the user is not 

interested in the quality at the transmitter but he would like to have the best possible quality at the receiving end. 

If you have a lot of noise on the channel and bit errors, then it is better to reduce the basic quality that is the bit-rate for 

speech coding, and to increase the bit-rate for error protection. 

This is presently being introduced in the network and it is a very good solution because it is much cheaper for the 

network operator than, let me say, improving the radio coverage inside buildings, because you would need additional 

base stations and so on. That improves the quality in terms of the basic quality and robustness against error you can 

still use the phone in places where you could not use it before, but the bandwidth is still 3.4 kHz. 

Audio example 1: AMR narrowband and wideband 

There is the wideband version which we have had since 2000 – roughly eight years. There is the standard and the AMR 

wideband codec has nine different modes between 6.6 and 24 kbits/s, and there is one mode at 12.5 kbits/s which we 

can use in GSM. Everywhere in the network, where we have a grey area, we have GSM coverage and we could use 

wideband coding with more or less the same bit rate as with AMR narrowband coding. 

Let’s listen to the narrowband quality and the wideband quality. [Examples of recorded speech played] I think you 

recognised the difference: the intelligibility is much better than in the narrowband sound case, but it is the codec which 

was designed for speech. 

Audio example 2: AMR codecs music and speech 

Now let’s listen if we apply music to the AMR narrowband codec, and then apply music to the AMR wideband coding – 

but we carefully check the bit-rate, and we now allowed the bit-rate to be somewhat higher. We could not transport 

that quality within GSM because in GSM the bit-rate should be at 12.65 but, if you have a UMTS network, we are allowed 

to increase the bit-rate a little. Let’s listen to some music. [Examples of recordings of music played] The 7 kHz is better, 

but it is not good, so we can do more with super-wideband. 

There is a version called AMR wideband-plus, with a bandwidth of 14 kHz and, interestingly, there is a mode with almost 

the same bit-rate, that is the progress that we have made in coding technology which means that we have to increase 

complexity, but we can also increase the quality. Let’s listen once more to the music. [Music played] That seems to be 

better but the phone is made for speech communication and the question is, why should we increase to AMR 

wideband plus for speech? 

Let’s listen once more to a different speech sample, in narrowband, wideband and super-wideband. [Examples of 

recorded speech played] Amazingly, even for speech, super-wideband gives some clear improvement. 



The introduction of wideband speech in GSM 

What is the present situation? I asked two leading operators in Germany last week, with the following result. Vodafone 

is presently studying – as are other operators in Europe – the topic of wideband speech but the problem is that the 

terminals are not yet commercially available but there are some under test. If these terminals become available in 

sufficient quantity, then implementation is an options. The introduction of super-wideband might become an option if 

we have UMTS LTE, so that sounds quite optimistic. 

The introduction of wideband speech in GSM 

The answer from T-Mobile, the second largest operator in Germany, was that they have equipped some parts of the 

network with the AMR wideband codec and they plan to offer this service in some parts of the network in the third 

quarter of this year, if the terminals become commercially available – and they say that they are waiting for the 

terminals. That sounds very optimistic, something might happen there this year. 

The compatibility and complexity problem 

If we start in some parts of the network – if we start at all – then you can clearly see that we would have to rely first on 

GSM, and only to a certain part on UMTS. That requires new terminals on both sides and it requires modification in the 

network, we have two worlds – the narrowband world and the wideband world – why should a customer buy a 

wideband phone if does not know anyone who has one? That is the same situation as applied with fax machines many 

years ago, and the solution is costly. In any case, there will be a very long transition period until – if ever – the whole 

telephone network will have been converted into a wideband service. However, there is a chance of competition with 

the fixed network, with the voice-over IP phones, if we succeed in implementing that in the wireless world. 

In the transition phase: artificial bandwidth extension (BWE) for supporting user acceptance 

There is not a solution but a helper in the transition phase, 

and that helper is called artificial bandwidth extension (BWE), 

which could increase user acceptance if, at the receiving end, 

we succeed in artificially increasing the bandwidth. As a 

sound engineer, you would say that that is impossible: we 

learned from Shannon that, if you have thrown the 

frequencies away, you don’t reconstruct them at the receiver – 

but it is voice, and the receiver is the ear. You can do a lot of 

tricks and there is still a great deal of redundancy in the signal, 

such that you can extract from the narrow band signal at the 

receiving end some information to produce the higher 

frequencies artificially, where the ear is not that sensitive as at 

the lower frequency. It is a mixture of speech recognition, of 

estimation and speech synthesis and there is some theory but 

I can tell you that most listeners prefer artificial wideband 

extension in comparison to the narrowband transmission. Foreign guests, who speak and understand German a little, 

say that it is much easier to understand. 

BWE: the theory 

There is some theory behind that. I will not go into too much detail but we can have a discussion after the talk on the 

individual equations. 

Audio example 3: telephone speech without and with BWE 

I would like to play you an example of artificial bandwidth extension at the receiving site. Here, we have narrowband 

speech at 3.4 kHz, more or less. The lower limit is 200 or 300 Hz and we artificially increase the bandwidth at the 

receiving end but we have no additional side information – we do not transmit side information. [Example of speech 

played] You might argue whether that is better or not. It gives some improvement in quality and probably also of 

intelligibility – it is a compromise, but it might help to introduce the wideband service. 


Bandwidth extension with hidden side information 

Time domain BWE with 600 bit/s of side information 

But there is another solution, which is to use artificial 

wideband extension but, this time, we allow some side 

information but we do not have a channel for transmitting it. 

The idea is to use watermarking techniques to hide the 

enhancement bits for artificial wideband extension at the 

receiver in the bit-stream, such that we have wideband 

terminals which produce a certain amount of additional 

information which is hidden in the bit-stream. The bit-stream 

is still compatible with the narrowband terminal, you can use 

the old terminal as it is and you should not notice any 

difference. However, the more sophisticated new terminal is 

capable of extracting the side information. The nice thing 

with this approach is that you don’t need to modify the 

network at all. As long as the terminals are in the same 

network, you just need to sell the customer two new phones 

and say, ‘this is the wideband phone’. This seems to be a very 

attractive solution. 

The missing frequencies are reproduced here such that at the transmitter we have some wideband processing and we 

extract parameters to re-synthesise at the receiver the higher frequencies. We receive the side information due to the 

watermarking process and we do some decoding. There, we exploit the insensitivity of the human ear at the higher 

frequencies and, in the simplest cases, we have just the noise generator and digital filter which is controlled, and we 

produce the frequencies between 3.4 and 7 kHz. That works quite well with speech. In this case we used 600 bit/s for 

wideband extension with this simplified module we contributed recently to one of the latest ITU coding standards for 

voice-over IT. There is bandwidth extension with side information and we use this model. 

Wideband speech with hidden side information 

We have played with it a little and the solution looks like this. You have the enhanced wideband encoder running at 16 

kHz, and you have the low power. You modify the coder such that you can hide there the parameter which has been 

extracted in the high-pass band. The normal decoder does not know about it and is not irritated – you don’t recognise 

the degradation in the quality and the enhanced decoder extracts the parameters, does the synthesis, adds it to the 

decoded signal, and you get wideband. 

The secret behind that is simple to explain but difficult to understand. We have code books there and their address 

base is huge – therefore, at the transmitter, where we are looking for the number of the joke, we cannot check all the 

jokes – we have a limited set of addresses that are allowed. We therefore allow different code books at the transmitter 

and the sophisticated receiver finds out which code book is used and the standard decoder can decode it because it is 

compatible – as it uses only allowed addresses in the vector space. 

Example 4: enhanced codec 

We applied it to several codecs. We have enhanced narrowband codec with hidden information and I would like to play 

one example of this. This is the AMR codec – and with the red cross, I don’t say ‘AMR plus’, but I say, ‘AMR – Red Cross’. 

As you know the Red Cross gives help in situations where you need to improve something. This is the enhanced fullrate 

codec 12.2 kbits, with a hidden data stream of 600 bits/s, but you can increase it for that codec to up to 2 kbits/s. 

You can hide 2 kbits – you can do anything with the 2 kbits, and we are using it here for wideband extension. Let us 

compare it to dedicated wideband standard at the same bit rate. We start with the narrowband first. 

The quality measured, by the way, is the PESQ measure here, where low numbers are bad and higher numbers are 

good. Here, it seems to be comparable in terms of the objective quality which reflects with perceptual quality. 

[Examples of speech played] For speech, it is almost as good – and that could be a solution if only parts of the network 



have been converted, to introduce wideband services everywhere, where you have the GSM phone. However, that is 

not a standard but just an idea from research. 

Mobile audio – communication 

Now we have nice coding schemes, you might introduce wideband, super-wideband, or artificial extension or whatever, 

but we have adverse conditions on the radio channel and we need error protection. There are very sophisticated 

techniques. You have heard about turbo-coding, turbo error protection, turbo error correction and error concealment. 

4 Turbo error protection 

The turbo concept can be extended, which was originally defined for two channel codes which help each other in an 

iterative way at the receiver. It can be extended to a channel decoder and to a source decoder. At the receiving end, we 

have a channel decoder which produces soft information – and soft information means that the channel decoder does 

not produce 0 and 1, but it produces reliability information. It says, eventually it is 0 or 1, with the probability. Then we 

have a soft decision source decoder, where the decoder exploits some residual redundancy which is still in the 

parameters. If we model the speech tract, the vocal tract, then the parameters evolve more or less smoothly, because 

we do the analysis every 20 milliseconds, 50 times per second, and the vocal track doesn’t make any jumps. 

There is still correlation in the parameters – and redundancy in terms of the distribution. The parameters are not white 

noise. This can be used such that we do a preliminary parameter decoding and we exploit the redundancy on the level 

of the parameters, and we feed that information back – it is called extrinsic information – through the channel decoder 

and the channel decoder tries once more. There is a second decoding using the knowledge from the channel end, the 

additional auxiliary information from the source decoder. 

In this slide, the source decode has better information and can improve once more and so, by several iterations, you 

have iterative source channel decoding and we can improve tremendously. 

Example 5: iterative source-channel decoding 

Let’s listen to one example of how we can improve by 

spending at the receiving end on just additional signal 

processing complexity. If the channel is clear, we do not need 

it but, if the channel is getting worse, we can improve it by 

additional processing. [Example of speech recording played] 

In this case, we used just plain PCM to demonstrate the 

concept. [Music played] We can maintain the quality if we 

are allowed to use this complexity. 

Mobile audio – communication 

Now I would like to share a vision of what more we can do 

than just introducing wideband and artificial wideband 

extensions. 

Iterative source-channel decoding (ISCD) 

This is a comparison with state-of-the-art decoding, where we 

have hard-decision decoding that is table look-up decoding 

in the source decoder, or soft decoding in the source decoder 

without iteration. We then do some iterations – here, in this 

case, it is 10 iterations – and we see a significant 

improvement. This is the parameter signal-to-noise ratio, the 

quality of the filter coefficients of the speech model, for 

example. This is the channel quality here, and we have a 

good channel here, and a bad channel. If we have a demand 

for a certain quality, we can maintain it, even in very adverse 

channel conditions. 


4 Vision: ambience audio communication 

The vision is very simple: let’s call it ambience audio communication – or, you could say, stereo of binaural telephony. 

What is it good for? We would like to have a situation where the quality is as in a face-to-face communication. 

In binaural telephony you transmit, so to speak, a picture of the audio environment, which is interesting if there is more 

than a single person at one end, because you have spatial information. What we need is the wireless transmission of 

two channels in both directions. 

Ambience audio conferencing 

There is a special situation where you might agree that this could be useful: attending a meeting, for example. Everyone 

who has attended telephone conferences which take two hours, with 10 participants from seven countries, knows that 

it would be desirable to have such a device. You might send your dummy head to the meeting, or there could be some 

dummy head, with two microphones and a loudspeaker. In this case, we have binaural transmission only in one 

direction. Sitting here, in the environment B, you get the directivity, the spatial information. You have to have wideband 

or super-wideband. If you use that, you will save a lot of travelling costs and time: you will like it, I can tell you – we 

have some experience of it. By the way, environment A is the meeting room at the airport and environment B is a nice 

spot at the beach where you can attend the meeting. 

The experimental binaural headset 

We have done some experiments with the dummy head. Here are the ear canals and the microphones are placed there 

so that we can make measurements. The transparency you get is amazing. You cannot buy it yet, but you can get an 

idea about it. 

Wireless (narrowband) speech communication 

There are some nice devices, including the earset from Bang & Olufsen: it is still mono and it is still narrowband. It has a 

microphone here and only one earpiece, but such implementation is not far off. You get some impression about how 

attractive and relaxing audio communication could be. 

Ambience audio communication 

We need stereo coding, and there is stereo coding even for the AMR wideband plus. There is an mpeg codec and there 

are recent developments with new versions and additions of codecs that will be available by the end of this year, so we 

can do it. 

5. Conclusion: flawless mobile audio communication 

My conclusion is that flawless mobile audio communication is feasible because the coding technology is available, or 

will soon be available. We have wideband coding and super-wideband coding in mono and stereo and, if we have to 

use the GSM network, there is a bit rate for the wideband codec which can be transmitted over GSM. There are higher 



bit rates which are more transparent for non-voice signals. In the not too distant future, UMTS LTE might be available 

within the next two or three years. We have AMR wideband-plus and higher bit rates, and new stereo codecs. In the 

future, we will no longer need to distinguish between speech and audio. 

The wireless network technology is not a bottleneck 

The wireless network technology is not a bottleneck. Even if there is a severe coverage problem, we have the GSM 

network. We have a fallback solution, and we have the fallback modes of the AMR codec. Even with a GSM network, 

we can employ bandwidth extension eventually, with hidden side information which supports the introduction which 

is much cheaper but which gives a clear impression of wideband coding. 

Finally, if we have UMTS LTE, we have plenty of bit rate and there is no alternative to true wideband coding: if you can 

afford to do true wideband coding, the quality is better than that of artificial wideband extension, and better than the 

lower rates of the AMR codec. 

We can preserve the quality of adverse channel conditions if we apply processing power – a turbo process at the 

receiving end. Therefore, my conclusion is that a mobile phone does not have to sound like an old telephone but can 

sound significantly better and we can hopefully expect terrific improvements in the future – even in the near future. 

There is a vision that binaural stereo communication might become a new philosophy. That is an interesting discussion. 

Is it just a further step in improving the quality, or is it a new world? If you remember the introduction of the Walkman, 

until then no one had thought of running through the forest with stereo equipment, but how it has changed our way 

of listening to music. It might be that binaural telephony will do a similar job, and wideband is the first step to 

increased intelligibility and naturalness, such that it is more or less comparable with face-to-face communication. 

From plain old telephony to flawless mobile audio communication 

I would like to finish my talk with a recent statement by Peter Isberg from Sony Ericsson. He said: 

“Despite the challenges, wideband will be the most significant quality upgrade in telephone history. Mobile phones will surpass 

traditional fixed line phones in terms of speech quality.” 

Thank you very much. [Applause] 



Michael Walker: Thank you, Peter, for that splendid talk. Peter has agreed to take questions, so we have the 

opportunity to tease out more information. 

John Lowe (Institution of Mechanical Engineers): Thank you, Peter – it is a fascinating future that you have 

described. What worries me is the duplication of standards between the three territories of the Far East, Europe and 

North America. Could you fill us in on the prospect of some compatibility or singularity of direction? 

Peter Vary: Yes, that is a very good question. We have many standards – perhaps too many – but this is also evolution. 

We are in the happy situation that, in the meantime, we have worldwide agreement on two sides. One is the ITU 

(International Telecommunications Union), which is more or less responsible for fixed line, voice-over IP business. 

On the other side we have what is called the 3GPP (Third Generation Partnership Programme). They talk to each other 

and take over the standards we have for cellular radio meanwhile in the ITU world. Things are getting better. 

There will be many different standards but there will be a convergence, I am pretty sure but, for reasons of compatibility, 

you will need to have the old codecs. I have a collection of some old phones – my first one is the Motorola shown on 

the slide, and it still works. If I switch it on, it says that it is no longer compatible with the system, but it works. We have 

to keep the compatibility but, on the other side, it is not too expensive because it is just software – but, saying that it is 

‘just software’ means that most of the signalling processing is carried out on a programmable signal processor in the 

mobile phone. You have a lot of memory there and selecting a different codec is just a matter of selecting a different 

part of the memory where you have the programme for the codec A, B, C, D, E. It is not that difficult, but it is more 

difficult than in the old world where you just had one or two different versions of A-law PCM and Mu-law PCM. It is 

becoming more difficult but it is not too expensive. 

Professor Ralph Benjamin (Visiting Professor, Bristol University): Right at the beginning, you mentioned the 

importance of understanding the physiological constraints on speech generation as a guide to the optimum use of a 

limited number of bits in the information, which will probably be even more important in speech extension, bandwidth 

expansion, or in turbo decoding. However, this is only one of probably three separate elements because you also have 

the constraints of language and dialect. In American southern states, people talk with a long drawl; other languages are 

totally different from English and, in one extreme, some African languages consist of a lot of staccato clicks. The features 

you have to encode depend rather critically on this. 

A third feature might be that different elements in your speech may be of different sensitivity in terms of recognition 

and understanding, or acceptability by the user. You may need rather a clever combination of those three features to 

make the best use of the information in encoding in the first place, or in knowing which preamble or supporting 

parameters are required to tell you how to do your bandwidth extension. Thank you. 

Peter Vary: The standardisation of the different speech codecs is always based on subjective listening tests. In the 

codec competition, different companies are proposing codec candidates and there is no objective measure that is so 

reliable that you can rely on the objective measure. Therefore, we need subjective listening tests, which are very 

expensive, in different languages, with native listeners and native speakers. That, first of all, is a necessary constraint 

which is fulfilled for the coding part. 

For bandwidth extension, I can tell you that it makes a big difference to apply bandwidth extension for German or 

French or Japanese. You hear the variation and it might work better for one language than for another. You could 

implement a language switch, or language recognition, or something like that. That is why the artificial bandwidth 

extension without any side information is only the second best solution: it gives you some wideband impression and 

sometimes it works well. If you could adapt it to the speaker, then it would be very nice. 

Therefore, the proposal to add side information – in that case, the concept will hide these bits in the bit-stream, but we 

first have to get the bits. This is done in such a way that, at the transmit side, we have the higher frequency band and 

then we apply there locally the artificial bandwidth extension and we compare it with the original. We then transmit 

the correction terms as hidden information to the receiver. If you have a strange language there, hopefully the 



bandwidth extension module at the transmitter side will do the job. However, there is still much work to do and the 

listening tests have to be done on a broad basis. 

Perhaps I could just add a further comment to the last question. If we are moving towards UMTS LTE, and we are 

allowed to increase somewhat the bit rate, then the codecs will become more and more transparent to any kind of 

strange dialect. 

Andy Evans (Cable & Wireless EAUS): I just wondered how much interest there is in the standards forums in actually 

adopting these different codecs in future mobile standards – particularly LTE? 

Peter Vary: As far as I understand it – and I guess Mike can comment on that – one of the main reasons for the NGMN 

initiative is that there are too many standards and that the operators are surprised that there are the solutions A, B, C 

and D and you have to implement them all and then you will see on the market whether it is a good solution or not, 

and whether it is taken or not. The operators try to steer the standardisation and to settle all the critical issues, including 

the IPR method, before the standard is written. 

Michael Walker: I can add to that. One of the big costs in the business is that, because of the standardisation process, 

you often have multiple solutions for the same problem. All those solutions get implemented in the equipment and 

that is a waste of the resource. If we are going to see technologies like this, which could actually offer the user much 

more benefit, having multiple choices for basic functionality, then we have to resolve that problem. 

Dr Tim Moulsley (HJM Ltd): I am an independent consultant but formerly I was with Philips. 

Peter Vary: Yes, you were a colleague of mine. 

Tim Moulsley: Just picking up the point we are on now, which is looking at the standards for codecs, I wonder how 

the take-over of an all-IP network, both in fixed and in mobile, will affect this kind of debate. That would tend to push 

the codec to the application level, where there is much more flexibility about which codec standard you actually have, 

than if it is in as part of the wireless network or part of the telecoms network itself. Would you like to comment on that? 

Peter Vary: My impression is that voice-over IP is actually the driving force to introduce wideband in cellular. The point 

is that no one has the chance to listen to a phone in the shop. If you go to a shop to buy a telephone, you have no idea 

and you don’t think that it makes any sense to listen to the quality – because a phone has a certain quality and it is a 

phone. 

Now, however, we see some experienced users having voice-over IP communication. Voice-over IP can be significantly 

worse or sometimes much better. Many things are going on there. We have Skype and we have SIP telephones. 

We have the evolution of cordless telephones, the DECT telephones. They have now decided to implemented 

wideband the codec and you can buy DECT telephones which have two connections to networks – one traditional 

network, the telephone network, and one to the DSL router at your home. If you connect it to the DSL router, you have 

wideband speech with excellent quality. 

You have greater flexibility in voice-over IP and this will sort out which codecs will survive. There is also a debate 

between the mobile community and the IP community – that is, ITU on one side and 3GPP – as to whether we should 

use a universal codec in future in both fixed and wireless networks. There is some hope because they are talking to 

each other to get the same codec under a 3GPP number and under an ITU number. Some voice-over IP operators are 

already using AMR wideband. 

Professor Chris Guy (University of Reading): There is rather a chicken and egg situation here, because you have the 

operators and the handset manufacturers but who will jump first and implement it? One has to go before the other. 

Peter Vary: I try have tried to support this topic of wideband for many years, because I like it. I have been involved in 

many talks and contacts with manufacturers and operators. What you usually hear is that the manufacturers are saying 

that the operator does not require it, while the operator is saying that there are no terminals. I heard the same story just 

last week. 

I said to the operators that, if they introduced wideband, that would be some improvement compared to their 

competitors, and people would talk for longer. They would do more business if they had wideband codec. That is what 


I said five years ago and what I hear now is that they are saying that they don’t like people talking that much because 

they have flat rates – so they should not talk at all. [Laughter] 

Andrew Poh (Qualcomm): I am speaking in my own personal capacity and I have three questions. The first is just for 

clarification on my part because I may have missed something. You mentioned the turbo error protection and the use 

of iterative source channel coding. Do you see this as something that you would use on the receiving side of the 

handset? You will probably incur some latency, going through the turbo error protection, as you go through a few 

iterations. 

Peter Vary: You can apply it to any standard transmission system. We have applied it just to plain GSM. You do not 

need to change the transmitter but you can do it just at the receiving end by additional processing and exchange of 

information between the channel decoder and the source decoder. However, if you study that in greater detail, you will 

discover that you can further improve if you modify the transmitter but it is a matter of the environment in which you 

apply it. If we were starting to think about a new radio standard, then we would say that you should not use Gray 

coding, for example, index mapping at the transmitter, but there are better solutions. We can improve the existing 

system. 

Andrew Poh: Is that applicable for real time volume, since there will be some latency if you go to - ? 

Peter Vary: There are two sources of latency. One is the interleaver and we have it there, and it is sufficiently large. 

The second is some latency due to processing but, in any case, you have to do the processing before the next packet 

arrives and so you have to increase the processing speed. The turbo decoding as such, therefore, will not increase the 

latency. 

Andrew Poh: My second question follows on from the question asked earlier. There was the question about the use 

of AMR wideband and I guess this has been debated in the mobile community for quite some time. The operators will 

always argue that no one is really willing to pay any extra for it and so they have been dragging their heels, and we have 

seen that happening. They always say that it will be this year, but it never happens. 

With the introduction or standardisation of AMR wideband and 3GPP, it is taking an awfully long time. Companies like 

Skype, as we know, have this week introduced a new wideband speech codec. Is it possible that doing that on a 

packet-switch network, using perhaps a Windows mobile phone and just downloading the codec, would be quicker 

than getting the industry together to introduce AMR wideband over a circuit switched connection? 

Peter Vary: Yes, that is what we hear. There is a consensus that if we have UMTS LTE it will be packet transmission and 

then there will be greater flexibility and more convergence with the internet world. However, we should be careful here 

because latency is an issue, the headers are an issue, and the frequency/economy is an issue, as is the energy efficiency. 

If you require short latency, the packets are short but you have the header and you could discover that you double the 

number of bits you have to transmit and therefore you need to improve protocols, header compression and techniques 

like that – at least on the air interface, and then you go into the fixed network. I am pretty sure that the future will be IP. 

Andrew Poh: My third question is something which you perhaps touched upon in your very excellent presentation: 

3GPP works like something like distributed speech recognition. Obviously, they also debated whether to use something 

for speech communication or whether to go for a totally different codec which is optimised for machine recognition, a 

speech recognition type of thing. Would you be able to comment on the use of a codec for speech recognition? 

Peter Vary: The idea is to do the speech recognition task not in the mobile but to have in the mobile just the feature 

extraction: you don’t transmit the speech, but you extract the features. You save computational power in the mobile 

and you have a very powerful processor in the fixed network. The idea is not that bad, but I am not sure. I am not sure 

about speech recognition at all. We have been hearing for years that there will be a breakthrough within the next one, 

two or three years. As the quality is hopefully increasing in the network, if you have wideband coding, the question is 

why should we do the parameter extraction in the mobile and the recognition task in the central switching office? 

If we check the bit rates for a codec like the AMR codec, you will see that roughly 50 per cent of the bit rate is for the 

parameters of the vocal tract and the model, and this is exactly the information you need for speech recognition. You 

will not save that much in terms of bit rate. I know that there is standardisation and that there are some very nice, 

interesting research topics, but I do not really see that as the future of speech recognition. I don’t know. 



Matthew Baker (Philips Research): At the beginning of your presentation, you described the original model for the 

voice codecs, based around two filters modelling broadly the vocal tract. As we move towards new, higher data rate 

communication systems, like UMTS LTE, there may perhaps be greater use of the system not for listening to speech but 

for music and video. Do you see a need for new codec models built around filters or parameterisations perhaps based 

on musical instruments or other sound sources than the vocal tract? 

Peter Vary: I have two answers to that. There is a nice European research project called FLEXCODE – like flexible 

coding. If you type that in your WEB browser, you will end up with the server in Aachen and there is a nice project with 

KTH, Bastiaan Kleijn and with Nokia Ericsson and France Telecom. We tried to design a universal codec which might be 

used in the future, which could be the future codec – I don’t know. In the standardisation world, we observe presently 

the development that we take a standard codec – for example, there is an ITU codec, G.729, which has 8 kbits/s. On top 

of that bit rate, there is then additional bit rate, up to 12 to 14, 16, 18 up to 32 kbits/s. The add-on, beyond 12 to 14 

kbits/s, is transform coding, so what we are seeing there is the base layer. It is a hierarchical coding scheme. If you 

transmit only the 8 kbits/s you can transmit speech. However, if the affordable bit rate is higher, you can have 

transparent quality for music. 

On top of the base layer, there is transform coding – techniques we know from audio coding. The reasoning behind 

that is that you could imagine, let us say, a broadcast service from a central station, and some of the subscribers have a 

DSL connection and would like to have the full bit rate, while some just have a GSM phone and they have a reduced bit 

rate, or just the base layer. For reasons of compatibility, that seems to be a good idea. However, you clearly see a 

convergence of speech coding and audio coding, which is mostly frequency domain-based coding. 

John Lowe: This question will involve Mike as well. It is appropriate that Keith Davis is here in particular. From my own 

background knowledge, Peter, I find what you have talked about this evening very exciting. However, we are in the 

hallowed halls here where they are doing something much bigger than this particular technology subject, which is 

encouraging young people to take up engineering. I suspect that the situation in your industry is no different than it is 

in mechanical engineering, where we have a shortage of young people at whatever level you might choose. Can we 

use this sort of exciting development to enhance the attraction of young people into engineering? And what, Mike, are 

Vodafone doing within this industry – and I am not particularly thinking of Vodafone but the industry as a whole – in 

this country and in others, particularly in Europe, to attract more young people? Can we use this to aid Keith Davis’s 

efforts, and those efforts taking place at the Institution of Mechanical Engineers and other places? 

Peter Vary: I can speak for Aachen University, where we have what we call the ‘science truck’. This is a truck which we 

drive to schools and then demonstrate experiments there, from mechanical engineering, electrical engineering, 

chemical engineering – all kinds, from all the faculties we have. From my group, we have an experiment there which is 

called ‘mobile radio’, where the pupils can have hands-on and listen to radio transmissions with bit errors and without 

bit errors, and vocoders. We try to attract them. We see the problem. We have open days, but we find that it is better 

to drive to the schools and give some lectures and show some experiments. 

John Lowe: If I could ask you to be generic, I know that taking technology to schools in individual areas works. I also 

run an industrial museum and we try to do that, with hands-on works and so on. However, I was looking for the general 

lessons that we can share across the broader picture. We cannot go into every school with a science truck – and I know 

our schools reasonably well. 

Peter Vary: I think we should educate the teachers. In their study schedules, there should be more engineering 

science, because the teachers do not know enough about engineering. 

John Lowe: I am really looking for practical help to make that happen. 

Michael Walker: Exactly on that point of helping the teachers, there is a project in the UK called Project Enthuse, which 

was started by the Wellcome Trust, and we are a member of that. The idea of Project Enthuse is that we provide 

continuous professional education to science teachers. We bring science teachers into the National Learning Centre 

and other places and we send engineers from industry to that centre and show those science teachers how their 

science is being applied today in industry. They can then take that back to the schools, to make their lessons perhaps 

more interesting to the pupils, to stimulate them to go on to study science and engineering at university. It aims to add 

that extra to the course. To go to your specific question, the Academy could take lectures like this, or the key parts of 


them and perhaps leave out some of the more difficult equations which we didn’t get into here anyway, and take that 

into the schools. That is basic physics, with a bit of biology there. 

John Lowe: Thank you. That will do – otherwise we could spend two days discussing this. 

Professor Jiangzhou Wang (University of Kent): In classes, we teach students that the binaries of speech signal are 

3.4 kHz. If my understanding is correct, according to your seminar, the binaries of speech signal should be 7 kHz instead 

of 3.4 kHz, in order to have good quality for the speech signal. Should we update our lecture notes in the future and 

teach our students that 3.4 kHz is not enough and that the binary for speech signal should be 7 kHz in order to have a 

high quality speech signal? What do you think? 

Peter Vary: I agree, but the reality is that we have the wideband coding standard for ISDN from 1985. The patterns are 

no longer valid, however, but we now see the first implementation, 20 years later, in DECT. It takes too long. 

John Ellis (London Artificial Intelligence Club): If doing speculative, blue sky research, would you be doing anything 

towards quantum computing and entanglement ideas of quantum mechanics, so that a sub-particle over here affects 

one over there? 

Peter Vary: That is a good idea, and I showed the picture of the dummy head at the meeting. I had the idea that, if 

you moved your head, the dummy head should also move. There are lots of improvements you could think about. 

Michael Walker: Peter, you started off showing a €1 phone, and we know how it got to €1 with standard codecs. 

Have you done work to look at what actually is the increase in cost and building materials in introducing wideband 

codecs? 

Peter Vary: As a university group, we are interested in cost and complexity but we are doing calculations in terms of 

computational complexity and power consumption. We have a big project at my university called the Cluster of 

Excellence, and the title is Ultra-High-Speed Mobile Information and Communication. That is a project of 20 chairs at 

my university, ranging from micro-electronics to applications. We have the guys from computer science there, and also 

from micro-electronics, and we talk to each other. 

We are acutely aware that the cost is very critical, and in addition to cost there is energy efficiency and spectral 

efficiency. We know that we have to improve – and we said the perceived order of magnitude, by one order of 

magnitude, in terms of bit rate, and not just the bit rate but what you perceive. We also have to improve in terms of 

costs. So all I would say is yes, at the university, we are really aware of that and we discuss it with our students, but we 

really cannot make a business plan for Vodafone and tell you how much you will have to invest. 

Michael Walker: But the costs in terms of complexity is fine, or energy increase – 

Peter Vary: But by the way, this funny proposal with the hidden bits is due to the awareness of the complexity and 

costs if you introduce AMR wideband. It is nice to say that we should have it there, but we know that you have to 

change each base station and the channel codec, which is very expensive. You also have to change the protocols and 

the transcoding units and so on. It is very expensive, and perhaps this could be a contribution to the discussion, to 

have cheaper solutions. 

Michael Walker: If there are no further questions, let me thank Peter for a very stimulating and interesting presentation, 

and a great conversation or discussion afterwards. I would also like to thank the audience for the very interesting 

question. Thank you very much. [Applause] 


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