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E-raamat: Cognitive Communications - Distributed Artificial Intelligence (DAI), Regulatory Policy & Economics, Implementation: Distributed Artificial Intelligence (DAI), Regulatory Policy and Economics, Implementation [Wiley Online]

Edited by David Grace (University of York), Edited by Honggang Zhang (Zhejiang University)

Formaat: 500 pages
Ilmumisaeg: 31-Aug-2012
Kirjastus: John Wiley & Sons Inc
ISBN-10: 1118360311
ISBN-13: 9781118360316

Teised raamatud teemal:

Wiley Online
Hind: 186,08 €*
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Formaat: 500 pages
Ilmumisaeg: 31-Aug-2012
Kirjastus: John Wiley & Sons Inc
ISBN-10: 1118360311
ISBN-13: 9781118360316

Teised raamatud teemal:

Rohkem infot Wiley Online kohta

Raamatu kodulehekülg: https://onlinelibrary.wiley.com/doi/book/10.1002/9781118360316

"This book discusses in-depth the concept of distributed artificial intelligence (DAI) and its application to cognitive communications In this book, the authors present an overview of cognitive communications, encompassing both cognitive radio and cognitive networks, and also other application areas such as cognitive acoustics. The book also explains the specific rationale for the integration of different forms of distributed artificial intelligence into cognitive communications, something which is oftenneglected in many forms of technical contributions available today. Furthermore, the chapters are divided into four disciplines: wireless communications, distributed artificial intelligence, regulatory policy and economics and implementation. The book contains contributions from leading experts (academia and industry) in the field.Key Features: Covers the broader field of cognitive communications as a whole, addressing application to communication systems in general (e.g. cognitive acoustics and Distributed Artificial Intelligence (DAI) Illustrates how different DAI based techniques can be used to self-organise the radio spectrum Explores the regulatory, policy and economic issues of cognitive communications in the context of secondary spectrum access Discusses application and implementation of cognitive communications techniques in different application areas (e.g. Cognitive Femtocell Networks (CFN) Written by experts in the field from both academia and industry Cognitive Communications will bean invaluable guide for research community (PhD students, researchers) in the areas of wireless communications, and development engineers involved in the design and development of mobile, portable and fixed wireless systems., wireless network design engineer. Undergraduate and postgraduate students on elective courses in electronic engineering or computer science, and the research and engineering community will also find this book of interest. "--

"This book discusses in-depth the concept of distributed artificial intelligence (DAI) and its application to cognitive communications In this book, the authors present an overview of cognitive communications, encompassing both cognitive radio and cognitive networks, and also other application areas such as cognitive acoustics. The book also explains the specific rationale for the integration of different forms of distributed artificial intelligence into cognitive communications, something which is oftenneglected in many forms of technical contributions available today. Furthermore, the chapters are divided into four disciplines: wireless communications, distributed artificial intelligence, regulatory policy and economics and implementation. The book contains contributions from leading experts (academia and industry) in the field.Key Features: Covers the broader field of cognitive communications as a whole, addressing application to communication systems in general (e.g. cognitive acoustics and Distributed Artificial Intelligence (DAI) Illustrates how different DAI based techniques can be used to self-organise the radio spectrum Explores the regulatory, policy and economic issues of cognitive communications in the context of secondary spectrum access Discusses application and implementation of cognitive communications techniques in different application areas (e.g. Cognitive Femtocell Networks (CFN) Written by experts in the field from both academia and industry Cognitive Communications will be an invaluable guide for research community (PhD students, researchers) in the areas of wireless communications, and development engineers involved in the design and development of mobile, portable and fixed wireless systems., wireless network design engineer. Undergraduate and postgraduate students on elective courses in electronic engineering or computer science, and the research and engineering community will also find this book of interest. "--

This book discusses in-depth the concept of distributed artificial intelligence (DAI) and its application to cognitive communications

In this book, the authors present an overview of cognitive communications, encompassing both cognitive radio and cognitive networks, and also other application areas such as cognitive acoustics. The book also explains the specific rationale for the integration of different forms of distributed artificial intelligence into cognitive communications, something which is often neglected in many forms of technical contributions available today. Furthermore, the chapters are divided into four disciplines: wireless communications, distributed artificial intelligence, regulatory policy and economics and implementation. The book contains contributions from leading experts (academia and industry) in the field.

Key Features:

Covers the broader field of cognitive communications as a whole, addressing application to communication systems in general (e.g. cognitive acoustics and Distributed Artificial Intelligence (DAI)

Illustrates how different DAI based techniques can be used to self-organise the radio spectrum

Explores the regulatory, policy and economic issues of cognitive communications in the context of secondary spectrum access

Discusses application and implementation of cognitive communications techniques in different application areas (e.g. Cognitive Femtocell Networks (CFN)

Written by experts in the field from both academia and industry

Cognitive Communications will be an invaluable guide for research community (PhD students, researchers) in the areas of wireless communications, and development engineers involved in the design and development of mobile, portable and fixed wireless systems., wireless network design engineer. Undergraduate and postgraduate students on elective courses in electronic engineering or computer science, and the research and engineering community will also find this book of interest.

List of Figures

xiii

List of Tables

xxv

About the Editors

xxvii

Preface

xxix

PART I INTRODUCTION

1 Introduction to Cognitive Communications

(16)

David Grace

1.1 Introduction

(1)

1.2 A New Way of Thinking

(2)

1.3 History of Cognitive Communications

(2)

1.4 Key Components of Cognitive Communications

(1)

1.5 Overview of the Rest of the Book

(5)

1.5.1 Part 2: Wireless Communications

(1)

1.5.2 Part 3: Application of Distributed Artificial Intelligence

(1)

1.5.3 Part 4: Regulatory Policy and Economics

(1)

1.5.4 Part 5: Implementation

(1)

1.6 Summary and Conclusion

(5)

References

(5)

PART II WIRELESS COMMUNICATIONS

2 Cognitive Radio and Networks for Heterogeneous Networking

(34)

Haesik Kim

Aarne Mammela

2.1 Introduction

(7)

2.1.1 Historical Sketch

(2)

2.1.2 Cognitive Radio and Networks

(1)

2.1.3 Heterogeneous Networks

(4)

2.2 Cognitive Radio for Heterogeneous Networks

(11)

2.2.1 Channel Sensing and Network Sensing

(1)

2.2.2 Interference Mitigation

(4)

2.2.3 Power Control

(6)

2.3 Applying Cognitive Networks to Heterogeneous Networks

(10)

2.3.1 Network Policy for Coexistence of Different Networks

(2)

2.3.2 Cooperation Mechanisms

(2)

2.3.3 Network Resource Allocation

(3)

2.3.4 Self-Organization Mechanisms

(1)

2.3.5 Handover Mechanisms

(2)

2.4 Performance Evaluation

(3)

2.5 Conclusion

(3)

References

(3)

3 Channel Assignment and Power Allocation Algorithms in Multi-Carrier-Based Cognitive Radio Environments

(40)

Musbah Shaat

Faouzi Bader

3.1 Introduction

(1)

3.2 The Orthogonal Frequency-Division Multiplexing (OFDM) Transmission Scheme

(2)

3.2.1 Why OFDM is Appropriate for CR

(1)

3.3 Resource Management in Non-Cognitive OFDM Environments

(2)

3.3.1 Single User OFDM Systems

(1)

3.3.2 Multiple User OFDM Systems (OFDMA)

(1)

3.3.3 Resource Allocation Algorithms in Non-Cognitive OFDM Systems

(1)

3.4 Resource Management in OFDM-Based Cognitive Radio Systems

(30)

3.4.1 Algorithms Dealing with In-Band Interference

(1)

3.4.2 Algorithms Dealing with Mutual Interference

(1)

3.4.3 System Model

(2)

3.4.4 Problem Formulation

(1)

3.4.5 Resource Management in Downlink OFDM-Based CR Systems

(12)

3.4.6 Resource Management in Uplink OFDM-Based CR Systems

(12)

3.5 Conclusions

(5)

References

(4)

4 Filter Bank Techniques for Multi-Carrier Cognitive Radio Systems

(26)

Yun Cui

Zhifeng Zhao

Rongpeng Li

Guangchao Zhang

Honggang Zhang

4.1 Introduction

(1)

4.2 Basic Features of Filter Banks-Based Multi-Carrier Techniques

(4)

4.2.1 Introduction to the Filter Bank System

(1)

4.2.2 The Polyphase Structure of Filter Banks

(1)

4.2.3 Basic Structure of Filter Banks-Based Multi-Carrier Systems

(1)

4.3 Adaptive Threshold Enhanced Filter Bank for Spectrum Detection in IEEE 802.22

(10)

4.3.1 Multi-Stage Analysis Filter Banks for Spectrum Detection

(2)

4.3.2 Complexity and Detection Precision Analysis

101

(2)

4.3.3 Spectrum Detection in IEEE 802.22

103

(3)

4.3.4 Power Estimation with Adaptive Threshold

106

(2)

4.4 Transform Decomposition for Spectrum Interleaving in Multi-Carrier Cognitive Radio Systems

108

(7)

4.4.1 FFT Pruning in Cognitive Radio Systems

108

(2)

4.4.2 Transform Decomposition for General DFT

110

(1)

4.4.3 Improved Transform Decomposition Method for DFT with Sparse Input Points

111

(3)

4.4.4 Numerical Results and Computational Complexity Analysis

114

(1)

4.5 Remaining Problems in Filter Banks-Based Multi-Carrier Systems

115

(2)

4.6 Summary and Conclusion

117

(2)

References

117

(2)

5 Distributed Clustering of Cognitive Radio Networks: A Message-Passing Approach

119

(26)

Kareem E. Baddour

Oktay Ureten

Tricia J. Willink

5.1 Introduction

119

(3)

5.1.1 Inter-Node Collaboration in Decentralized Cognitive Networks

119

(1)

5.1.2 Scalability Issues and Overhead Costs

120

(1)

5.1.3 Self-Organization Based on Distributed Clustering

120

(2)

5.2 Clustering Techniques for Cognitive Radio Networks

122

(2)

5.3 A Message-Passing Clustering Approach Based on Affinity Propagation

124

(2)

5.4 Case Studies

126

(12)

5.4.1 Clustering Based on Local Spectrum Availability

127

(5)

5.4.2 Sensor Selection for Cooperative Spectrum Sensing

132

(6)

5.5 Implementation Challenges

138

(2)

5.6 Conclusions

140

(5)

References

140

(5)

PART III APPLICATION OF DISTRIBUTED ARTIFICIAL INTELLIGENCE

6 Machine Learning Applied to Cognitive Communications

145

(18)

Aimilia Bantouna

Kostas Tsagkaris

Vera Stavroulaki

Panagiotis Demestichas

Giorgos Poulios

6.1 Introduction

145

(1)

6.2 State of the Art

146

(2)

6.3 Learning Techniques

148

(10)

6.3.1 Bayesian Statistics

148

(2)

6.3.2 Supervised Neural Networks (NNs)

150

(3)

6.3.3 Self-Organizing Maps (SOMs): An Unsupervised Neural Network

153

(4)

6.3.4 Reinforcement Learning

157

(1)

6.4 Advantages and Disadvantages of Applying Machine Learning to Cognitive Radio Networks

158

(1)

6.5 Conclusions

159

(4)

Acknowledgement

160

(1)

References

160

(3)

7 Reinforcement Learning for Distributed Power Control and Channel Access in Cognitive Wireless Mesh Networks

163

(32)

Xianfu Chen

Zhifeng Zhao

Honggang Zhang

7.1 Introduction

163

(2)

7.2 Applying Reinforcement Learning to Distributed Power Control and Channel Access

165

(26)

7.2.1 Conjecture-Based Multi-Agent Q-Learning for Distributed Power Control in CogMesh

165

(11)

7.2.2 Learning with Dynamic Conjectures for Opportunistic Spectrum Access in CogMesh

176

(15)

7.3 Future Challenges

191

(1)

7.4 Conclusions

192

(3)

References

192

(3)

8 Reinforcement Learning-Based Cognitive Radio for Open Spectrum Access

195

(36)

Tao Jiang

David Grace

8.1 Open Spectrum Access

195

(1)

8.2 Reinforcement Learning-Based Spectrum Sharing in Open Spectrum Bands

196

(12)

8.2.1 Learning Model

196

(4)

8.2.2 Basic Algorithms

200

(1)

8.2.3 Performance

200

(8)

8.3 Exploration Control and Efficient Exploration for Reinforcement Learning-Based Cognitive Radio

208

(21)

8.3.1 Exploration Control Techniques for Cognitive Radios

208

(10)

8.3.2 Efficient Exploration Techniques and Learning Efficiency for Cognitive Radios

218

(11)

8.4 Conclusion

229

(2)

References

230

(1)

9 Learning Techniques for Context Diagnosis and Prediction in Cognitive Communications

231

(26)

Aimilia Bantouna

Kostas Tsagkaris

Vera Stavroulaki

Giorgos Poulios

Panagiotis Demestichas

9.1 Introduction

231

(1)

9.2 Prediction

232

(21)

9.2.1 Building Knowledge: Learning Network Capabilities and User Preferences/Behaviours

232

(16)

9.2.2 Application to Context Diagnosis and Prediction: The Case of Congestion

248

(5)

9.3 Future Problems

253

(1)

9.4 Conclusions

254

(3)

References

255

(2)

10 Social Behaviour in Cognitive Radio

257

(28)

Husheng Li

10.1 Introduction

257

(1)

10.2 Social Behaviour in Cognitive Radio

258

(9)

10.2.1 Cooperation Formation

258

(3)

10.2.2 Channel Recommendations

261

(6)

10.3 Social Network Analysis

267

(14)

10.3.1 Model of Recommendation Mechanism

267

(1)

10.3.2 Interacting Particles

268

(5)

10.3.3 Epidemic Propagation

273

(8)

10.4 Conclusions

281

(4)

References

281

(4)

PART IV REGULATORY POLICY AND ECONOMICS

11 Regulatory Policy and Economics of Cognitive Radio for Secondary Spectrum Access

285

(36)

Maziar Nekovee

Peter Anker

11.1 Introduction

285

(1)

11.2 Spectrum Regulations: Why and How?

286

(1)

11.3 Overview of Regulatory Bodies and Their Inter-Relation

287

(4)

11.3.1 ITU

287

(1)

11.3.2 CEPT/ECC

288

(1)

11.3.3 European Union

289

(1)

11.3.4 ETSI

290

(1)

11.3.5 National Spectrum Management Authority

291

(1)

11.4 Why Secondary Spectrum Access?

291

(2)

11.5 Candidate Bands for Secondary Access

293

(3)

11.5.1 Terrestrial Broadcasting Bands

294

(1)

11.5.2 Radar Bands

294

(1)

11.5.3 IMT Bands

295

(1)

11.5.4 Military Bands

296

(1)

11.6 Regulatory and Policy Issues

296

(8)

11.6.1 UK Regulatory Environment

300

(1)

11.6.2 US Regulatory Environment

301

(1)

11.6.3 European Regulatory Environment

302

(1)

11.6.4 Regulatory Environments Elsewhere

303

(1)

11.7 Technology Enablers and Options for Secondary Sharing

304

(4)

11.7.1 Cognitive Radio

304

(2)

11.7.2 Technology Options for Secondary Access

306

(2)

11.8 Economic Impact and Business Opportunities of SSA

308

(5)

11.8.1 Stakeholders and Economic of SSA

309

(1)

11.8.2 Use Cases and Business Models

310

(3)

11.9 Outlook

313

(1)

11.10 Conclusions

314

(7)

Acknowledgements

315

(1)

References

315

(6)

PART V IMPLEMENTATION

12 Cognitive Radio Networks in TV White Spaces

321

(38)

Maziar Nekovee

Dave Wisely

12.1 Introduction

321

(3)

12.2 Research and Development Challenges

324

(11)

12.2.1 Geolocation Databases

324

(3)

12.2.2 Sensing

327

(3)

12.2.3 Beacons

330

(1)

12.2.4 Physical Layer

330

(1)

12.2.5 System Issues

331

(4)

12.2.6 Devices

335

(1)

12.3 Regulation and Standardization

335

(8)

12.3.1 Regulation

335

(3)

12.3.2 Standardization

338

(5)

12.4 Quantifying Spectrum Opportunities

343

(3)

12.5 Commercial Use Cases

346

(8)

12.6 Conclusions

354

(5)

Acknowledgement

355

(1)

References

355

(4)

13 Cognitive Femtocell Networks

359

(36)

Faisal Tariq

Laurence S. Dooley

13.1 Introduction

359

(2)

13.2 Femtocell Network Architecture

361

(11)

13.2.1 Underlay and Overlay Architectures for Femtocell Networks

362

(4)

13.2.2 Home Femtocell and Enterprise Femtocell

366

(3)

13.2.3 Access Mechanism: Closed, Open and Hybrid Access

369

(2)

13.2.4 Possible Operating Spectrum

371

(1)

13.3 Interference Management Strategies

372

(9)

13.3.1 Cross-Tier Interference Management

373

(3)

13.3.2 Intra-Tier Interference Management

376

(5)

13.4 Self Organized Femtocell Networks (SOFN)

381

(7)

13.4.1 Self-Configuration

383

(1)

13.4.2 Self-Optimization

383

(5)

13.4.3 Self-Healing and Self-Protection

388

(1)

13.5 Future Research Directions

388

(3)

13.5.1 Green Femtocell Networks

388

(1)

13.5.2 Communication Hub for Smart Homes

389

(1)

13.5.3 MIMO-Based Interference Alignment for Femtocell Networks

389

(1)

13.5.4 Enhanced FFR

390

(1)

13.5.5 CoMP-Based Femtocell Network

391

(1)

13.5.6 Holistic Approach to SOFN

391

(1)

13.6 Conclusion

391

(4)

References

391

(4)

14 Cognitive Acoustics: A Way to Extend the Lifetime of Underwater Acoustic Sensor Networks

395

(22)

Lu Jin

Defeng (David) Huang

Lin Zou

Angela Ying Jun Zhang

14.1 The Concept of Cognitive Acoustics

395

(2)

14.2 Underwater Acoustic Communication Channel

397

(4)

14.2.1 Propagation Delay

397

(1)

14.2.2 Severe Attenuation

397

(1)

14.2.3 Ambient Noise

398

(3)

14.3 Some Distinct Features of Cognitive Acoustics

401

(1)

14.3.1 Purposes of Deployment

401

(1)

14.3.2 Grey Space

402

(1)

14.3.3 Cost of Field Measurement and System Deployment

402

(1)

14.4 Fundamentals of Reinforcement Learning

402

(2)

14.4.1 Markov Decision Process

402

(1)

14.4.2 Reinforcement Learning

403

(1)

14.4.3 Q-Learning

403

(1)

14.5 An Application Scenario: Underwater Acoustic Sensor Networks

404

(6)

14.5.1 System Description

404

(2)

14.5.2 State Space, Action Set and Transition Probabilities

406

(1)

14.5.3 Reward Function

407

(2)

14.5.4 Routing Protocol Discussion

409

(1)

14.6 Numerical Results

410

(4)

14.7 Conclusion

414

(3)

Acknowledgements

414

(1)

References

414

(3)

15 CMOS RF Transceiver Considerations for DSA

417

(48)

Mark S. Oude Alink

Eric A.M. Klumperink

Andre B.J. Kokkeler

Gerard J.M. Smit

Bram Nauta

15.1 Introduction

417

(4)

15.1.1 Terminology

418

(2)

15.1.2 Transceivers for DSA: More than an ADC and DAC

420

(1)

15.1.3 Flexible Software-Defined Transceiver

421

(1)

15.1.4 Why CMOS Transceivers?

421

(1)

15.2 DSA Transceiver Requirements

421

(2)

15.3 Mathematical Abstraction

423

(3)

15.4 Filters

426

(2)

15.4.1 Integrated Filters

426

(1)

15.4.2 External Filters

427

(1)

15.5 Receiver Considerations and Implementation

428

(8)

15.5.1 Sub-Sampling Receiver

429

(1)

15.5.2 Heterodyne Receivers

430

(2)

15.5.3 Direct-Conversion Receivers

432

(4)

15.6 Cognitive Radio Receivers

436

(13)

15.6.1 Wideband RF-Section

436

(1)

15.6.2 No External RF-Filterbank

437

(10)

15.6.3 Wideband Frequency Generation

447

(2)

15.7 Transmitter Considerations and Implementation

449

(2)

15.8 Cognitive Radio Transmitters

451

(5)

15.8.1 Improving Transmitter Linearity

451

(1)

15.8.2 Reducing Harmonic Components

452

(1)

15.8.3 The Polyphase Multipath Technique

453

(3)

15.9 Spectrum Sensing

456

(6)

15.9.1 Analogue Windowing

458

(1)

15.9.2 Channelized Receiver

459

(1)

15.9.3 Crosscorrelation Spectrum Sensing

459

(2)

15.9.4 Improved Image and Harmonic Rejection Using Crosscorrelation

461

(1)

15.10 Summary and Conclusions

462

(3)

References

462

(3)

Index

465

Dr. David Grace, University of York, UK David Grace is Head of Communications Research Group and Co-Director of York-Zhejiang Lab for Cognitive Radio and Green Communications. He received his MEng and DPhil degrees from York in 1993 and 1999 respectively. David's current research interests include cognitive radio and green communications, specifically spectrum assignment aspects, and cognitive networking.

Dr. Honggang Zhang, Zhejiang University, China Honggang Zhang is a Full Professor at the Department of Information Science and Electronic Engineering, Zhejiang University, China. He received the Ph.D. degree in Electrical Engineering from Kagoshima University, Japan, in March 1999. Prior to that, he received the Bachelor of Engineering and Master of Engineering degrees, both in Electrical Engineering, from Huazhong University of Science & Technology (HUST), China, in 1989, and Lanzhou University of Technology, China, in 1992, respectively.

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