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Index
COVER TITLE PAGE COPYRIGHT PAGE DEDICATION PAGE PREFACE PART I: INTRODUCTION TO COGNITIVE RADIOS
1 INTRODUCTION
1.1 INTRODUCTION 1.2 SIGNAL PROCESSING AND COGNITIVE RADIOS 1.3 SOFTWARE-DEFINED RADIOS 1.4 FROM SOFTWARE-DEFINED RADIOS TO COGNITIVE RADIOS 1.5 WHAT THIS BOOK IS ABOUT 1.6 SUMMARY
2 THE COGNITIVE RADIO
2.1 INTRODUCTION 2.2 A FUNCTIONAL MODEL OF A COGNITIVE RADIO 2.3 THE COGNITIVE RADIO ARCHITECTURE 2.4 THE IDEAL COGNITIVE RADIO 2.5 SIGNAL PROCESSING CHALLENGES IN COGNITIVE RADIOS 2.6 SUMMARY
3 COGNITIVE RADIOS AND DYNAMIC SPECTRUM SHARING
3.1 INTRODUCTION 3.2 INTERFERENCE AND SPECTRUM OPPORTUNITIES 3.3 DYNAMIC SPECTRUM ACCESS 3.4 DYNAMIC SPECTRUM LEASING 3.5 CHALLENGES IN DSS COGNITIVE RADIOS 3.6 COGNITIVE RADIOS AND FUTURE OF WIRELESS COMMUNICATIONS 3.7 SUMMARY
PART II: THEORETICAL FOUNDATIONS
4 INTRODUCTION TO DETECTION THEORY
4.1 INTRODUCTION 4.2 OPTIMALITY CRITERIA: BAYESIAN VERSUS NON-BAYESIAN 4.3 PARAMETRIC SIGNAL DETECTION THEORY 4.4 NONPARAMETRIC SIGNAL DETECTION THEORY 4.5 SUMMARY
5 INTRODUCTION TO ESTIMATION THEORY
5.1 INTRODUCTION 5.2 RANDOM PARAMETER ESTIMATION: BAYESIAN ESTIMATION 5.3 NONRANDOM PARAMETER ESTIMATION 5.4 SUMMARY
6 POWER SPECTRUM ESTIMATION
6.1 INTRODUCTION 6.2 PSD ESTIMATION OF A STATIONARY DISCRETE-TIME SIGNAL 6.3 BLACKMAN–TUKEY ESTIMATOR OF THE POWER SPECTRUM 6.4 OTHER PSD ESTIMATORS BASED ON MODIFIED PERIODOGRAMS 6.5 PSD ESTIMATION OF NONSTATIONARY DISCRETE-TIME SIGNALS 6.6 SPECTRAL CORRELATION OF CYCLOSTATIONARY SIGNALS 6.7 SUMMARY
7 MARKOV DECISION PROCESSES
7.1 INTRODUCTION 7.2 MARKOV DECISION PROCESSES 7.3 FINITE-HORIZON MDPs 7.4 INFINITE-HORIZON MDPs 7.5 PARTIALLY OBSERVABLE MARKOV DECISION PROCESSES 7.6 SUMMARY
8 BAYESIAN NONPARAMETRIC CLASSIFICATION
8.1 INTRODUCTION 8.2 K-MEANS CLASSIFICATION ALGORITHM 8.3 X-MEANS CLASSIFICATION ALGORITHM 8.4 DIRICHLET PROCESS MIXTURE MODEL 8.5 BAYESIAN NONPARAMETRIC CLASSIFICATION BASED ON THE DPMM AND THE GIBBS SAMPLING 8.6 SUMMARY
PART III: SIGNAL PROCESSING IN COGNITIVE RADIOS
9 WIDEBAND SPECTRUM SENSING
9.1 INTRODUCTION 9.2 WIDEBAND SPECTRUM SENSING PROBLEM 9.3 WIDEBAND SPECTRUM SCANNING PROBLEM 9.4 SPECTRUM SEGMENTATION AND SUBBANDING 9.5 WIDEBAND SPECTRUM SENSING RECEIVER 9.6 SUBBAND SELECTION PROBLEM IN WIDEBAND SPECTRUM SENSING 9.7 A REDUCED COMPLEXITY OPTIMAL SUBBAND SELECTION FRAMEWORK WITH AN ALTERNATIVE REWARD FUNCTION 9.8 MACHINE-LEARNING AIDED SUBBAND SELECTION POLICIES 9.9 SUMMARY
10 SPECTRAL ACTIVITY DETECTION IN WIDEBAND COGNITIVE RADIOS
10.1 INTRODUCTION 10.2 OPTIMAL WIDEBAND SPECTRAL ACTIVITY DETECTION 10.3 WIDEBAND SPECTRAL ACTIVITY DETECTION 10.4 WAVELET TRANSFORM-BASED WIDEBAND SPECTRAL ACTIVITY DETECTION 10.5 WIDEBAND SPECTRAL ACTIVITY DETECTION IN NON-GAUSSIAN NOISE 10.6 WIDEBAND SPECTRAL ACTIVITY DETECTION WITH COMPRESSIVE SAMPLING 10.7 SUMMARY
11 SIGNAL CLASSIFICATION IN WIDEBAND COGNITIVE RADIOS
11.1 INTRODUCTION 11.2 SIGNAL CLASSIFICATION PROBLEM IN A WIDEBAND COGNITIVE RADIO 11.3 FEATURE EXTRACTION FOR SIGNAL CLASSIFICATION 11.4 A SIGNAL CLASSIFICATION ARCHITECTURE FOR A WIDEBAND COGNITIVE RADIO 11.5 BAYESIAN NONPARAMETRIC SIGNAL CLASSIFICATION 11.6 SEQUENTIAL BAYESIAN NONPARAMETRIC SIGNAL CLASSIFICATION 11.7 SUMMARY
12 PRIMARY SIGNAL DETECTION IN DSA COGNITIVE NETWORKS
12.1 INTRODUCTION 12.2 SPECTRUM SENSING PROBLEM IN DYNAMIC SPECTRUM SHARING CR NETWORKS 12.3 AUTONOMOUS SPECTRUM SENSING FOR DYNAMIC SPECTRUM SHARING 12.4 LIMITATIONS OF AUTONOMOUS SPECTRUM SENSING 12.5 COOPERATIVE SPECTRUM SENSING FOR DYNAMIC SPECTRUM SHARING 12.6 COOPERATIVE CHANNEL-STATE DETECTION 12.7 SUMMARY
13 SPECTRUM DECISION-MAKING IN DSA COGNITIVE NETWORKS
13.1 INTRODUCTION 13.2 PRIMARY CHANNEL DYNAMIC MODEL 13.3 SENSING DECISIONS IN DSS NETWORKS WITH AUTONOMOUS COGNITIVE RADIOS 13.4 SENSING DECISIONS IN COOPERATIVE DSS NETWORKS 13.5 SUMMARY
14 DYNAMIC SPECTRUM LEASING IN COGNITIVE RADIO NETWORKS
14.1 INTRODUCTION 14.2 DSL WITH DIRECT REWARDS TO PRIMARY USERS 14.3 DSL BASED ON ASYMMETRIC COOPERATION WITH PRIMARY USERS 14.4 SUMMARY
15 COOPERATIVE COGNITIVE COMMUNICATIONS
15.1 INTRODUCTION 15.2 COOPERATIVE SPECTRUM SENSING 15.3 COOPERATIVE SPECTRUM SENSING AND CHANNEL-ACCESS DECISIONS 15.4 COOPERATIVE COMMUNICATIONS STRATEGIES IN COGNITIVE RADIO NETWORKS 15.5 ASYMMETRIC COOPERATIVE RELAYING IN DSA COGNITIVE RADIOS 15.6 SUMMARY
16 MACHINE LEARNING IN COGNITIVE RADIOS
16.1 INTRODUCTION 16.2 ARTIFICIAL NEURAL NETWORKS 16.3 SUPPORT VECTOR MACHINES 16.4 REINFORCEMENT LEARNING 16.5 MULTIAGENT LEARNING 16.6 SUMMARY
APPENDIX A: NYQUIST SAMPLING THEOREM APPENDIX B: A COLLECTION OF USEFUL PROBABILITY DISTRIBUTIONS
B.1 UNIVARIATE DISTRIBUTIONS B.2 MULTIVARIATE DISTRIBUTIONS
APPENDIX C: CONJUGATE PRIORS REFERENCES INDEX END USER LICENSE AGREEMENT
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