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Signal processing for cognitive radios /
"This book covers power electronics, in depth, by presenting the basic principles and application details, and it can be used both as a textbook and reference book. Introduces the specific type of CR that has gained the most research attention in recent years: the CR for Dynamic Spectrum Access...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken, New Jersey :
Wiley,
2014.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- 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 OPPORTUNITIES3.3 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 SUMMARY6 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 INTRODUCTION8.2 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 FUNCTION9.8 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.