Lecture Series in Mobile Telecommunications and Networks (1583KB)

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From wireless networks to sensor networks and onward to networked embedded contrtol Application Layer Transport Layer Network Layer MAC Physical Layer Interference + Interference + Application Layer Transport Layer 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. The Royal Academy of Engineering 7
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? 8 The Royal Academy of Engineering 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
Page 1 and 2: Lecture Series in Mobile Telecommun
Page 3 and 4: Foreword This compilation brings to
Page 5 and 6: From wireless networks to sensor ne
Page 7: From wireless networks to sensor ne
Page 11 and 12: easons. In the internet, one never
Page 13 and 14: Implementation with laser pointers,
Page 15 and 16: here of laptops, and all these lapt
Page 17 and 18: adds a great deal of discrete compl
Page 19 and 20: Questions & Answers Mike Walker: Th
Page 21 and 22: Human beings will also evolve and w
Page 23 and 24: Welcome and introduction Professor
Page 25 and 26: ComReg Collection - Start 16/Apr/20
Page 27 and 28: evidence that people give in favour
Page 29 and 30: chunks of spectrum where you are in
Page 31 and 32: As an aside, I was reading a few of
Page 33 and 34: Of course, it is not just one mask,
Page 35 and 36: I apologise for hopping between top
Page 37 and 38: Questions & Answers Michael Walker:
Page 39 and 40: Nobody - believe you me, it came ou
Page 41 and 42: The second aspect of my comment is
Page 43 and 44: want to call it - that sits there a
Page 45 and 46: From plain old Telephony to flawles
Page 47 and 48: From plain old Telephony to flawles
Page 49 and 50: You can see that there is much room
Page 51 and 52: 1024, we transmit 10 bits, so to sp
Page 53 and 54: Bandwidth extension with hidden sid
Page 55 and 56: 4 Vision: ambience audio communicat
Page 57 and 58: Questions & Answers Michael Walker:
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I said five years ago and what I he
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them and perhaps leave out some of
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Lecture Series in Mobile Telecommunications and Networks (1583KB)

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