Software Radio Software Defined radio and Cognitive radio

Software Radio, Software Defined radio, and 

Cognitive radio 

Prof. Sao-Jie Chen 

Graduate Institute of Electronics Engineering 

National Taiwan University 

May 1 st , 2007

What is Cognitive Radio? 

A fully cognitive radio should have the ability to do the following: 

1. Tune to any available channel in the target band. 

2. Establish network communications and operate in all or part of the 

channel. 

3. Implement channel sharing and power control protocols which adapt 

to spectrum occupied by multiple heterogeneous networks. 

4. Implement adaptive transmission bandwidths, data rates, and error 

correction schemes to obtain the best throughput possible. 

5. Implement adaptive antenna steering to focus transmitter power in the 

direction required to optimize received signal strength. 

John Notor, “Radio Architectures for Unlicensed Reuse of Broadcast TV Channels,” 

Communications Design Conference, September, 2003.

Outlines 

1. Software Radio(SR) and Softwre Defined radio (SDR) 

2. Cognitive Radio (CR) 

3. CR Architecture 

4. CR1 Prototype 

5. CR Toolbox 

6. CR Case Study

Software Radio (SR) Architecture 

Source 

Set 

External Environment 

Evolution 

Support 

Channel 

Set 

Source 

Coding 

& 

Decoding 

Radio Node 

Service 

& 

Network 

Support 

INFO- 

SEC 

Joint Control 

Multiple Personalities 

Modem 

IF 

Processing 

RF/ 

Channel 

Access 

Channel Coding & Decoding 

[1] Mitola, J., “Software Radio Architecture: A Mathematical Perspective,” IEEE Journal on Selected Areas of 

Communication, April, 1999. 

[2] Mitola, “Software Radio Architecture Evolution: Foundations, Technology Tradeoffs, and Architecture 

Implications,” IEICE Tr. Commun. Vol. E83-B, June 2000.


• The Channel Set therefore includes multiple RF bands. Personal 

Communications System (PCS) base stations and mobile military radios 

can also use fiber and cable, also included in the channel set. 

• Channel coding encompasses programmable RF/ Channel Access, IF 

Processing, and Modem. Multiband antennas and RF conversion 

comprise the RF/ Channel Access function. RF functions may include 

interference suppression. 

• IF Processing may include filtering; further frequency translation; joint 

space-time equalization; integration of space diversity, polarization or 

frequency diversity channels; digital beamforming; and smart antennas . 

• Bitstream processing includes Forward Error Control (FEC) and 

softdecision decoding.


• Although many applications do not require Information Security 

(INFOSEC), there are incentives for its use. For example, authentication 

reduces fraud, and stream enciphering ensures privacy. INFOSEC may 

be null for some applications. 

• The source set may include voice, data, facsimile, video and multimedia. 

Some sources are physically remote from the radio node, e.g. connected 

via the Synchronous Digital Hierarchy (SDH), a Local Area Network 

(LAN), or other network through Service & Network Support. 

• Multimode radios generate multiple air interface waveforms (“modes”) 

using the modem, the RF channel modulator-demodulator. Waveforms 

may be in different bands and may span multiple bands. Each 

combination of band and mode is one of multiple personalities. Each 

personality combines RF band, channel set (e.g. control and traffic 

channels), air interface waveform, protocol, and related functions.


• In a software radio, all these functions are implemented using digital 

techniques in multithreaded multiprocessor software managed by a 

Joint Control function. Joint control assures system stability, error 

recovery, and isochronous streaming of voice and video. Joint Control 

may evolve towards autonomous selection of band, mode, and data 

format.

Software-Defined Radio (SDR) 

Software-Defined Radio (SDR) Forum, www.sdrforum.org

Software Radio

Outlines 





5. CR Toolbox 

6. CR Case Study

Cognitive Radio (CR) 

[2] J. Mitola III, “Software Radio Architecture Evolution,” IEICE Transactions on Communications, 

July 00.

Cognitive Cycle

Cognitive Cycle 

• Cognitive radio signifies a radio that employs model-based reasoning to 

achieve a specified level of competence in radio-related domains [5]. 

Cognitive radio architectures being investigated at KTH employ the 

cognition cycle as illustrated in the above figure [7]. 

• Cognitive radio is a goal-driven framework in which the radio 

autonomously observes the radio environment, infers context, assesses 

alternatives, generates plans, supervises multimedia services, and 

learns from its mistakes [7]. 

• In the Observe-stage, the cognitive radio observes its environment by 

parsing incoming information streams, i.e., the outside world stimuli, to 

recognize the context of its communications tasks. Incoming and 

outgoing multimedia content is parsed for the contextual cues 

necessary to infer the communications context (e.g., urgency). Thus, for 

example, the radio may infer that it is going for a taxi ride (with some 

probability) if the user ordered a taxi by voice and is located in a foreign 

country.


• The Orient-stage decides on the urgency of the communications in part 

from these cues in order to reduce the burden on the user. 

• The Plan-stage generates and evaluates alternatives, including 

expressing plans to peers and/or the network to obtain advice. 

• The Decide-stage allocates computational and radio resources to 

subordinate (conventional radio) software. 

• The Act-stage initiates tasks with specified resources for specified 

amounts of time. 

• Fundamental design rules by which SDR, sensors, perception, and AML 

are integrated to create Aware, Adaptive, and Cognitive Radios (AACR’s) 

with better Quality of Information (QoI) through capabilities to Observe 

(sense, perceive), Orient, Plan, Decide, Act and Learn (theOOPDALloop) 

in RF and user domains, transitioning from merely adaptive to 

demonstrably cognitive radio, CR.


• Architecture is a comprehensive, consistent set of design rules by 

which a specified set of components achieves a specified set of 

functions in products and services that evolve through multiple design 

points over time. 

[8] Joseph Mitola III, Software Radio Architecture, Wiley, 2000].

Outlines 





5. CR Toolbox 

6. CR Case Study

CR Architecture

CR Architecture 

• Characterized SDR Architecture 

• Developed Necessary Mathematical Foundations 

– Topological Model of Radio Architecture 

– Computability Proof for Bounded-Recursive Functions 

• Defined RKRL (Radio Knowledge representation Language) with Set- 

Theoretic Axioms 

• Invented the Cognition Cycle 

• Simulated the Contributions of a Notional Cognitive Radio 

– Spectrum Rental, Demand Shaping 

• Implemented a Research Prototype CR1 

– Simulated environment, not fully integrated, illustrative personalities 

• Articulated an Open Architecture Framework

Spectrum Pool Etiquette

Spectrum Pool Etiquette 

• Radio etiquette is the set of RF bands, air interfaces, protocols, spatial 

and temporal patterns, and high level rules of interaction that moderate 

the use of the radio spectrum. 

• Etiquette for spectrum pooling includes the spectrum renting process, 

assured backoff to authorized legacy radios, assured conformance to 

precedence criteria, an order-wire network, and related topics.

Implications of Spectrum Rental

Integration of Inter-Disciplinary Contributions

Topological Model of Dual-band Handset Streams

Topological Analysis 

• What are the domain and range? 

• Are they explicit? 

• What are the open sets? 

• What are the Unions, Intersections? 

• Is each map a homeomorphism? 

• Are the inverse images of open sets open?

SR Reference Platform Parameters

RKRL Overview

RKRL Overview 

• RKRL as a language has a set of metalevel micro-worlds that define 

admissible expressions: inferences, domain knowledge (the knowledge 

base), computational, and axiomatic models (the formal models). 

• RKRL also has a micro-world for each of its multiple knowledge bases, 

one for each major sub-domain of terrestrial wireless. 

• RKRL describes inferences that can be performed for task-domain 

automated reasoning. 

• These meso-world components describe and control conventional SDR 

components (hardware and software).

Cognitive Radio Meso-world Framework

RKRL Defines Knowledge Topology

PDA Architecture Domain

PDA Architecture Domain 

• In the above figure, S represents the internal model and W represents 

the external world, and we consider a radio’s signal in space, s(t) ∈ W 

as illustrated. 

• When the PDA receives the signal, it is converted to internal digital form 

by an ADC. 

• Thus, the signal is mapped first from the transmitted signal to a received 

signal, Receive(s), e.g. by the addition of noise and multipath. 

• Next it is digitized by an ADC to become the discrete signal x(i) ∈ S. 

• Thus, the map H from W to S is ADC(Receive(s(t))). Although H 

corresponds in part to a physically realizable device, the ADC, H is not a 

function that transforms signals. H is a map among subsets of S and W.

PDA Architecture Domain 

• In words, H states: “The analog signal in the time interval surrounding 

the continuous point s(t) ∈ W corresponds to the discrete point x(i) ∈ S 

at the sampling instant for N contiguous points.” 

• The corresponding map G from S to W is not a digital to analog 

converter. 

• The map G answers the question “How do subsets of x(i) map to 

subsets of s(t)?” This is answered in part by the Nyquist criterion. 

• If a signal s(t) is sampled at least as fast as specified by the Nyquist 

criterion, then the analog signal s(t) may be reconstructed uniquely from 

the digital samples, x(i), e.g. using Fourier series. 

• In addition, a received signal corresponds to some transmitted signal 

modified by propagation, so G(x(i)) = Propagation(Nyquist(x(i))). 

• G also is not a function. One need not be able to perform G on actual 

signals. G is the set-theoretic map that specifies which members of S 

correspond to which members of W. 

• Thus, G and H are ontological statements about the structure of the 

point sets s(t) and x(i).

Heterogeneous Knowledge Representation in RKRL

Heterogeneous Knowledge Representation in RKRL

Behavior as Homeomorphism 

• Inferences Map S to S, Actions Map S to W, and Sensing Maps W to S

Architecture Mapping

Environment-aware PDA 

[9] J. Mitola., “Cognitive Radio for Mobile Multimedia Communications,” MoMuC, Nov 99.

Outlines 





5. CR Toolbox 

6. CR Case Study

Cognitive Radio 1 (CR 1)

CR1 Rapid Prototype

CR1 Rapid Prototype 

• The CR1 rapid prototype is implemented as the Java object protoPDA. 

All PDAs are members of the class PDA that hosts the PDA design 

components. 

• Processing within the PDA is organized into pdaProcesses that are 

carried out sequentially for each of the cognitive radio’s phases and 

epochs. 

• The protoPDA acquires a phrase-sized block of stimuli from all sensors 

before attempting to interpret any of it. 

• The speech, text, and radio channel stimuli consist of at least one 

phrase, but each channel may offer multiple phrases as well. 

• Block processing reduces 162 ambiguities and allows set-associative 

recall to operate efficiently.

Mode Control Model

Mode Control Model 

• In the spectrum rental scenario, each mobile unit has to manage power 

pro-actively to avoid jamming legacy users when joining the rental 

network. 

• These contextual inputs would drive models that control selected states 

of the waveforms. The controlled entities include the SDR Forum radioentities 

defined in RKRL 0.3, including the modem. 

• These flow through a CIR/dataRate Model that CR1 has acquired by 

supervised learning, as illustrated in the above figure.

References: 

[1] J. Mitola, “Software Radio Architecture: A Mathematical Perspective,” IEEE Journal 

on Selected Areas of Communication, April, 1999. 

[2] J. Mitola, “Software Radio Architecture Evolution: Foundations, Technology 

Tradeoffs, and Architecture Implications,” IEICE Tr. Commun. Vol. E83-B, June 2000. 

[3] J. Mitola, “Software Radio: Technology and Prognosis,” Proc., IEEE National 

Telesystems Conference, 1992 

[4] J. Mitola, “Software Radio Architecture” IEEE Communications Magazine, May 1995 

[5] J. Mitola, Cognitive Radio, Licentiate Thesis, KTH (Royal Institute of Technology), 

Stockholm, 1999 

[6] G. Maguire and J. Mitola, “Cognitive Radio: Making PCS Personal,” IEEE PCS 

Magazine, August 99. 

[7] J. Mitola, “Cognitive Radio for Flexible Mobile Multimedia Communications,” Mobile 

Networks and Applications, 6, 435-441, 2001. 

[8] J. Mitola, Software Radio Architecture, Wiley, 2000. 

[9] J. Mitola, “Cognitive Radio for Mobile Multimedia Communications,” MoMuC, Nov 99. 

[10] J. Mitola, Cognitive Radio Architecture: The Engineering Foundations of Radio XML, 

Wiley 2006.

Outlines 





5. CR Toolbox 

6. CR Case Study

Cognitive toolbox 

1. Spectrum Sensing 

2. Policy Engine 

3. DFS (Dynamic Frequency Selection) 

4. Channel Characterization & Adaptation 

5. TPC (Transmit Power Control) 

6. Software Solutions 

Jeffrey Schiffer, “Cognitive Tools and Systems,” BWRC, Nov. 2004


1. Spectrum Sensing 

• The ability of the device to characterize the frequencies (bands) over 

which it is capable of operating 

• Includes the concept of signal analysis or identification 

• Provides input to interference mitigation algorithms 

2. Policy Engine 

• Has two major functions: 

– To check sensed environment against regulatory requirements 

– Set limits of operation based on selected spectrum


3. Dynamic Frequency Selection 

• Radios ability to choose a channel/frequency optimized for the desired 

payload 

• Can include multiband operation 

• Can be application/operation driven 

4. Channel Characterization 

• Channel error rate 

• Channel model correction 

• Channel usage


5. Transmit Power Control 

• Radio implementation controls output power of the device 

• For TV NPRM (Notice of Proposed Rule Making) should be based on 

adjacent channel power 

• Provides ability to optimize devices transmit power based on 

connectivity


6. Software Based Radios 

• Flexible solutions 

– “Tiered” implementations possible with the same hardware 

• Field upgradeable 

– Provides the possibility of a “renewable” solution for misbehaving 

systems 

– Activate functions after product ships 

• Separation of radio system functions from applications 

• Provides a path to single skew solutions


Summary 

• Cognitive & policy based radio solutions will be the norm for the future 

• Foundation is software based radios 

• Allows optimized use of spectrum and network capabilities 

• Major advantage is field upgradeability

Outlines 





5. CR Toolbox 

6. CR Case Study

Case Study: High Performance Cognitive Radio Platform with 

Integrated Physical and Network Layer Capabilities 

Bryan Ackland, et al., Technical Report, July 2005 

• The network-centric cognitive radio architecture under consideration in 

this project is aimed at providing a high-performance platform for 

experimentation with various adaptive wireless network protocols 

ranging from simple etiquettes to more complex ad-hoc collaboration. 

• Particular emphasis has been placed on high performance in a 

networked environment where each node may be required to carry out 

high throughput packet forwarding functions between multiple physical 

layers.

Cognitive Radio (CR) 

• Programmable radio systems that adapt to: 

Changing radio interference 

Availability of nearby collaborative nodes 

Changing protocols & standards 

Application requirements 

• By modifying 

Frequency, power, bandwidth 

Modulation, coding, MAC 

Network protocols 

• And coordinating with other cognitive systems to maximize spectral 

efficiency and fairness

Key Design Objectives for the CR Platform 

• multi-band operation, fast frequency scanning and agility; 

• software-defined modem including waveforms such as DSSS/QPSK and 

OFDM operating at speeds up to 50 Mbps; 

• packet processor capable of ad-hoc packet routing with aggregate 

throughput ~100 Mbps; 

• spectrum policy processor that implements etiquette protocols and 

algorithms for dynamic spectrum sharing.

Elements of a CR Prototype 

• The cognitive radio prototype’s architecture is based on four major 

elements: (1) MEMS-based tri-band agile RF front-end, (2) FPGA-based 

software defined radio (SDR); (3) FPGA-based packet processing engine; 

and (4) embedded CPU core for control and management. 

• These components will be integrated into a single prototype board 

which leverages an SDR implementation from Lucent Bell Labs as the 

starting point. A proof-of-concept demonstration board is planned for 

the end of year 2 (2006), and several prototype boards will full 

functionality are expected to be ready at the end of year 3 (2007).

Programmable Wireless Networks Research Goals: 

• Investigate Cognitive Radio Strategies & Spectrum Sharing Algorithms 

• Explore flexible, power efficient wireless architectures 

• Develop board level platform for system prototyping & subsequent 

distribution to research community

Platform Goals 

• Design & build cognitive radio platform that is 

- High performance 

- HW & SW Programmable 

- Physical, baseband & network layer adaptable 

- Support wide range of spectrum sharing scenarios 

• Leverage today’s high performance off-the-shelf components to build 

experimental platform with maximum utility & flexibility 

• Demonstrate architectures and components that will enable low cost, low 

power, flexible integrated circuit implementations in near future.

CR: Design Space

CR Capabilities 

• Spectrum scanning & frequency agility 

• Fast physical layer adaptation & power control to respond to changing 

local conditions 

• Flexible baseband & MAC switchable on a packet-by-packet basis (SDR) 

to provide interoperability with multiple radio technologies 

• Capable of higher layer spectrum etiquette or negotiation protocols 

• Simultaneous heterogeneous radio links 

• Protocol translation & routing to support heterogeneous and/or ad-hoc 

networks

CR Platform

Agile Tri-Band RF Front-End

Agile Tri-Band RF Front-End 

• Tri-band operation: 

- 700-800 MHz 

- 2.40-2.48 GHz ISM band 

- 5.15-5.825 GHz ISM and UN-II bands 

• 2 Transmit + 2 Receive channels for data + spectrum monitoring receiver 

• 20 MHz bandwidth on each channel tunable over band 

- Narrow band selection performed at baseband 

• 100mW transmit power (variable) per channel 

• Sensitivity & linearity to meet 802.11a

Baseband and Network Processor

Baseband and Network Processor 

• Interface to multiple radio channels 

• Real time spectral analysis 

• Support comparison of HW & SW baseband solution 

• MAC, protocol conversion, SAR, routing 

• Data rates (total) up to 100 Mb/s 

• Support novel reconfigurable architectures in baseband and network 

layers 

• Clean partitions between Baseband, NP and CR 

• Simple programming environment (not DSP) 

• Fast reconfiguration time (~μs)

SW Development Environment 

• Need efficient multi-user, multi-proc. compile & debug 

- Short learning curve for student SW developers 

• Linux OS with Gnu tool chain 

- Open source 

- Modular: I/O drivers can be installed without kernel modification or 

reboot 

- User friendly development environment 

• Simulink models compiled to VHDL and/or C

Software Radio Software Defined radio and Cognitive radio

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