Cognitive Radio Engineering

Cognitive Radio Engineering

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Overview

A cognitive radio is a transceiver which is aware of its environment, its own technical capabilities and limitations, and those of the radios with which it may communicate; is capable of acting on that awareness and past experience to configure itself in a way that optimizes its performance; and is capable of learning from experience. In a real sense, a cognitive radio is an intelligent communications system that designs and redesigns itself in real time.

Cognitive Radio Engineering is both a text and a reference book about cognitive radio architecture and implementation, intended for readers who want to design and build working cognitive radios. It takes the reader from conceptual block diagrams through the design and evaluation of illustrative prototypes. An important goal is to bridge the divide between radio engineers, who often have little experience with the computational resource and timing issues inherent in cognitive radios, and computer engineers who often are unaware of RF issues like dynamic range, intermodulation products, and acquisition time.

Following a brief overview of cognitive radio history and a high-level look at cognitive radio operation, the book presents a detailed study of cognitive engine design and analysis. After treating RF subsystems the book considers computational platforms and computation issues in cognitive radios, followed by system integration, evaluation methods for cognitive radio, and cognitive radio design for networking. The book concludes with coverage of cognitive radio applications in communications.

Product Details

ISBN-13: 9781613532119
Publisher: Institution of Engineering and Technology (IET)
Publication date: 10/31/2016
Series: Telecommunications Series
Pages: 264
Product dimensions: 7.20(w) x 10.20(h) x 0.80(d)

About the Author

Charles W. Bostian is the Alumni Distinguished Professor Emeritus of Electrical and Computer Engineering at Virginia Tech, USA. His students and he have made many contributions to cognitive radio, including developing the basic terminology and building some of the first working prototypes. Bostian has co-authored three other radio communications books, several book chapters, and a number of journal articles and conference presentations.


Nicholas J. Kaminski conducts research focused on extending the bounds of wireless technology by deploying targeted intelligence to act in harmony with flexible radio systems. He advances distributed radio intelligence through experimentation-based research and is co-principal investigator on several European projects that create and develop experimentation platforms and services for wireless research. He also furthers wireless communications by incorporating techniques for understanding communications from complex systems science.


Almohanad S. Fayez is a Software Engineer at Intel in Sort Test Technology Development (STTD) where he is involved in the design and development of Intel's next generation of silicon test modules. His interests include high performance computing, embedded systems, software defined radio, wireless networks while focusing on implementation and practical system considerations.

Table of Contents

Forward x

Acknowledgements xi

1 Introduction 1

1.1 What Is a Cognitive Radio and Why Is It Needed? 1

1.2 Book Coverage and Philosophy 2

1.3 The Origin of Cognitive Radio 3

1.4 Overview of Cognitive Radio Operation 5

1.5 An Illustrative Example of Cognitive Radio Application: Dynamic Spectrum Access in the Broadcast Television Bands 11

1.5.1 Introduction 11

1.5.2 Identifying Frequencies for Cognitive Radio Operation: TV Channel Occupancy in the United States 12

1.5.3 FCC Rules and Commercial Standards for Unlicensed Television Band Devices (TVBDs) 13

1.5.4 FCC Rule Implementation by the IEEE 802.11af Standard 16

1.5.5 TV White Space Databases 16

1.5.6 Standard ECMA-392 16

1.5.7 Cognitive Radio Design for U.S. TV White Space 17

1.6 Can a Radio Really Be Cognitive? 18

2 Cognitive Engine Design 23

2.1 Introduction 23

2.2 The Basic Function of a Cognitive Engine 24

2.3 Cognitive Engine Organization 25

2.3.1 Optimizer 27

2.3.2 Objective Analyzer 27

2.3.3 Ranker 28

2.3.4 Knowledge Base 28

2.3.5 Radio Interface 28

2.3.6 Sensor 28

2.3.7 User Interface 29

2.3.8 Controller 30

2.4 Tools and Techniques for CE Component Design 30

2.4.1 Machine Learning 30

2.4.2 Optimizers 35

2.4.3 Estimation 38

2.4.4 Sensing 39

2.5 Cognitive Engine Architecture 42

2.5.1 Broad Considerations 42

2.5.2 Monolithic Versus Distributed 44

2.5.3 Standards 45

2.5.4 Original CE Architecture 49

2.5.5 CSERE Architecture 53

2.6 Information Flow in Cognitive Engines 55

2.6.1 Example Use of Uncertainty Coefficient 57

2.7 Conclusion 60

3 RF Platforms for Cognitive Radio 65

3.1 Introduction 65

3.2 Preliminary Considerations in Choosing an RF Platform 66

3.3 RF Architectures 67

3.3.1 Receivers 67

3.3.2 Transmitter 68

3.4 Receiver RF Specifications 71

3.4.1 Introduction 71

3.4.2 Noise, Noise Performance, and Weak Signal Behavior 72

3.4.3 Strong Signal Behavior 77

3.5 Transmitter RF Specifications 85

3.6 MAC and Performance Considerations 88

3.7 Radio Frequency Integrated Circuits 90

3.7.1 Introduction 90

3.7.2 Example: RFM69CW 90

3.7.3 Computational Support for RFICs 92

3.8 Platforms for Software Defined Radio 94

3.8.1 Introduction 94

3.8.2 Packaged RF Front Ends and All-in-one Platforms 94

3.9 Conclusion 99

4 Cognitive Radio Computation and Computational Platforms 103

4.1 The Role of Computing and Cognitive Radio Architecture 103

4.2 Control Flow and Data Flow Computer Architectures 103

4.2.3 Control Flow Computing 103

4.2.2 Data Flow Computing 106

4.3 Overview of Computational Devices (GPP, DSP, FPGA) 107

4.3.1 Digital Signal Processors 107

4.3.2 General Purpose Processors 108

4.3.3 Field-programmable Gate Arrays 108

4.3.4 Alternative Computational Devices 109

4.3.5 Computational Heterogeneity 109

4.4 Models of Computation 110

4.4.1 Reactive and Real-time Systems 111

4.4.2 Data Flow Models of Computation 112

4.4.3 Process Algebra 119

4.4.4 Calculus of Communicating Systems and ?-calculus 122

4.5 Models of Computation Use 123

4.6 Conclusion 123

5 Integrating and Programming RF and Computational Platforms for Cognitive Radio 127

5.1 SDR Platforms 127

5.2 Choosing a Platform 128

5.2.1 Choosing Between RF Alternatives 128

5.2.2 Processor Choices 129

5.2.3 Benchmarks 130

5.2.4 Processor Interconnect 130

5.2.5 Other Considerations 131

5.3 Programming 131

5.3.1 Classic Approach 132

5.3.2 Model-Based Design 134

5.3.3 Application of Models-of-Computation 134

5.4 Concluding Remarks 142

6 Cognitive Radio Evaluation 147

6.1 Introduction 147

6.2 Performance Evaluation Principles 148

6.3 Metrics and Factors for Cognitive Radio Evaluation 149

6.3.1 Purpose 150

6.3.2 Language 151

6.3.3 Actions 154

6.4 Practical Evaluation Methods 154

6.4.1 Setup 155

6.4.2 Logging 155

6.4.3 Encoding 155

6.4.4 Interpolation 157

6.4.5 Alternative Approaches to Evaluation 159

6.5 Example Evaluation 159

6.5.1 Setup Phase 159

6.5.2 Logging Phase 160

6.5.3 Encoding Phase 161

6.5.4 Interpolation 163

6.6 Example Code 167

6.6.1 Free FEC Cognitive Radio 167

6.6.2 Fixed FEC Cognitive Radio 172

6.6.3 Interpolation Code 176

6.7 Conclusion 178

7 Cognitive Radio Design for Networking 179

7.1 Networks of Cognitive Radios Versus Cognitive Networks 179

7.2 Cognitive Network Goals 180

7.3 Interaction Methods for Cognitive Radios 182

7.3.1 Social Language 183

7.4 Components of interaction 187

7.4.1 Observability 187

7.4.2 Understanding 189

7.5 Analyzing Interactions 190

7.5.1 An Example Analysis 191

7.5.2 Analysis Results 192

7.6 Group Learning 194

7.7 Building a Cognitive Network with Social Language 196

7.7.1 MAC Layer Considerations 196

7.7.2 Behavior-based Design and Social Language 197

7.7.3 Tasks and Behaviors 197

7.7.4 Hardware Considerations and Implementation 198

7.7.5 Implementing Behaviors in Software and Hardware 200

7.7.6 Network Evaluation 207

7.7.7 The Entry Scenario 207

7.7.8 Social Learning 210

7.7.9 Total System Behavior 211

8 Cognitive Radio Applications 215

8.1 Introduction 215

8.2 Zoned Dynamic Spectrum Access 215

8.3 Cognitive WiFi and LTE Operation in TV White Space Spectrum 216

8.3.1 WiFi Frequency Translators 216

8.3.2 LTE Frequency Converters 221

8.4 LTE Cognitive Repeaters for Indoor Applications 221

8.5 Cognitive Radio and Cognitive Radar: Communications and Radar System Coexistence 222

8.5.1 Cognitive Radar 222

8.5.2 Legacy Radar and Communications System Coexistence 224

8.6 Ka Band Geostationary Satellite Applications 228

8.6.1 Introduction 228

8.7 Public Safety and Emergency First Responder Communication 232

8.7.1 Introduction 232

8.7.2 The Virginia Tech Public Safety Cognitive Radio 233

8.7.3 Current (2016) Situation 235

8.8 Cognitive Radio and Autonomous Vehicles 236

8.9 Smart Grids 239

Index 245

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