THE RADIO MANUAL
CONTENTS INTRODUCTION VISION: “BIG DATA” COGNITIVE RADIO: SYSTEM CONCEPTS SPECTRUM SENSING INTERFACE AND DATA STRUCTURES MATHEMATICAL MACHINERY CONVEX OPTIMIZATION GAME THEORY “BIG DATA” MODELED AS LARGE RANDOM MATRICES SAMPLE COVARIANCE MATRIX LARGE SAMPLE COVARIANCE MATRICES OF SPIKED POPULATION MODELS RANDOM MATRICES AND NONCOMMUTATIVE RANDOM VARIABLES PRINCIPAL COMPONENT ANALYSIS GENERALIZED LIKELIHOOD RATIO TEST (GLRT) BREGMAN DIVERGENCE FOR MATRIX NEARNESS SPECTRUM SENSING: BASIC TECHNIQUES CHALLENGES ENERGY DETECTION: NO PRIOR INFORMATION ABOUT DETERMINISTIC OR STOCHASTIC SIGNAL DETECTION IN WHITE NOISE: LOWPASS CASE TIME-DOMAIN REPRESENTATION OF THE DECISION STATISTIC SPECTRAL REPRESENTATION OF THE DECISION STATISTIC DETECTION AND FALSE ALARM PROBABILITIES OVER AWGN CHANNELS EXPANSION OF RANDOM PROCESS IN ORTHONORMAL SERIES WITH UNCORRELATED COEF?CIENTS: THE KARHUNEN-LOEVE EXPANSION SPECTRUM SENSING EXPLOITING SECOND-ORDER STATISTICS SIGNAL DETECTION FORMULATION WIDE-SENSE STATIONARY STOCHASTIC PROCESS: CONTINUOUS-TIME NONSTATIONARY STOCHASTIC PROCESS: CONTINUOUS-TIME SPECTRUM CORRELATION-BASED SPECTRUM SENSING FOR WSS STOCHASTIC SIGNAL: HEURISTIC APPROACH LIKELIHOOD RATIO TEST OF DISCRETE-TIME WSS STOCHASTIC SIGNAL ASYMPTOTIC EQUIVALENCE BETWEEN SPECTRUM CORRELATION AND LIKELIHOOD RATIO TEST LIKELIHOOD RATIO TEST OF CONTINUOUS-TIME STOCHASTIC SIGNALS IN NOISE: SELIN’S APPROACH STATISTICAL PATTERN RECOGNITION: EXPLOITING PRIOR INFORMATION ABOUT SIGNAL THROUGH MACHINE LEARNING KARHUNEN-LOEVE DECOMPOSITION FOR CONTINUOUS-TIME STOCHASTIC SIGNAL FEATURE TEMPLATE MATCHING CYCLOSTATIONARY DETECTION CLASSICAL DETECTION FORMALISM OF QUANTUM INFORMATION HYPOTHESIS DETECTION FOR COLLABORATIVE SENSING THE DATA MATRIX RANDOM MATRICES WITH INDEPENDENT ROWS THE MULTIVARIATE NORMAL DISTRIBUTION SAMPLE COVARIANCE MATRIX ESTIMATION AND MATRIX COMPRESSED SENSING THE MAXIMUM LIKELIHOOD ESTIMATION LIKELIHOOD RATIO TEST (WILKS’ TEST) FOR MULTISAMPLE HYPOTHESES LIKELIHOOD RATIO TEST GENERAL GAUSSIAN DETECTION AND ESTIMATOR-CORRELATOR STRUCTURE TESTS WITH REPEATED OBSERVATIONS DETECTION USING SAMPLE COVARIANCE MATRICES GLRT FOR MULTIPLE RANDOM VECTORS LINEAR DISCRIMINATION FUNCTIONS DETECTION OF CORRELATED STRUCTURE FOR COMPLEX RANDOM VECTORS HYPOTHESIS DETECTION OF NONCOMMUTATIVE RANDOM MATRICES WHY NONCOMMUTATIVE RANDOM MATRICES? PARTIAL ORDERS OF COVARIANCE MATRICES: A < B PARTIAL ORDERING OF COMPLETELY POSITIVE MAPPINGS: (A) < (B) PARTIAL ORDERING OF MATRICES USING MAJORIZATION: A ?B PARTIAL ORDERING OF UNITARILY INVARIANT NORMS: |||A||| < |||B||| PARTIAL ORDERING OF POSITIVE DE?NITE MATRICES OF MANY COPIES: K K=1 AK ?K K=1 BK PARTIAL ORDERING OF POSITIVE OPERATOR VALUED RANDOM VARIABLES: PROB(A ?X ?B) PARTIAL ORDERING USING STOCHASTIC ORDER: A ?ST B QUANTUM HYPOTHESIS DETECTION QUANTUM HYPOTHESIS TESTING FOR MANY COPIES LARGE RANDOM MATRICES LARGE DIMENSIONAL RANDOM MATRICES: MOMENT APPROACH, STIELTJES TRANSFORM AND FREE PROBABILITY SPECTRUM SENSING USING LARGE RANDOM MATRICES SYSTEM MODEL MARCHENKO-PASTUR LAW MOMENT APPROACH LIMITING SPECTRAL DISTRIBUTION LIMITS OF EXTREME EIGENVALUES CONVERGENCE RATES OF SPECTRAL DISTRIBUTIONS STANDARD VECTOR-IN, VECTOR-OUT MODEL GENERALIZED DENSITIES STIELTJES TRANSFORM BASIC THEOREMS LARGE RANDOM HANKEL, MARKOV AND TOEPLTIZ MATRICES INFORMATION PLUS NOISE MODEL OF RANDOM MATRICES GENERALIZED LIKELIHOOD RATIO TEST USING LARGE RANDOM MATRICES DETECTION OF HIGH-DIMENSIONAL SIGNALS IN WHITE NOISE EIGENVALUES OF (A + B)?1B AND APPLICATIONS CANONICAL CORRELATION ANALYSIS ANGLES AND DISTANCES BETWEEN SUBSPACES MULTIVARIATE LINEAR MODEL EQUALITY OF COVARIANCE MATRICES MULTIPLE DISCRIMINANT ANALYSIS CASE STUDIES AND APPLICATIONS FUNDAMENTAL EXAMPLE OF USING LARGE RANDOM MATRIX FREE DECONVOLUTION OPTIMAL PRECODING OF MIMO SYSTEMS MARCHENKO AND PASTUR’S PROBABILITY DISTRIBUTION CONVERGENCE AND FLUCTUATIONS EXTREME EIGENVALUES INFORMATION PLUS NOISE MODEL AND SPIKED MODELS HYPOTHESIS TESTING AND SPECTRUM SENSING ENERGY ESTIMATION IN A WIRELESS NETWORK MULTISOURCE POWER INFERENCE TARGET DETECTION, LOCALIZATION, AND RECONSTRUCTION STATE ESTIMATION AND MALIGNANT ATTACKER IN THE SMART GRID COVARIANCE MATRIX ESTIMATION DETERMINISTIC EQUIVALENTS LOCAL FAILURE DETECTION AND DIAGNOSIS REGULARIZED ESTIMATION OF LARGE COVARIANCE MATRICES REGULARIZED COVARIANCE ESTIMATES BANDING THE INVERSE COVARIANCE REGULARIZATION BY THRESHOLDING REGULARIZED SAMPLE COVARIANCE MATRICES OPTIMAL RATES OF CONVERGENCE FOR COVARIANCE MATRIX ESTIMATION BANDING SAMPLE AUTOCOVARIANCE MATRICES OF STATIONARY PROCESSES FREE PROBABILITY LARGE RANDOM MATRICES AND FREE CONVOLUTION VANDERMONDE MATRICES CONVOLUTION AND DECONVOLUTION WITH VANDERMONDE MATRICES FINITE DIMENSIONAL STATISTICAL INFERENCE LINEAR PROGRAMMING QUADRATIC PROGRAMMING SEMIDE?NITE PROGRAMMING GEOMETRIC PROGRAMMING LAGRANGE DUALITY OPTIMIZATION ALGORITHM INTERIOR POINT METHODS STOCHASTIC METHODS ROBUST OPTIMIZATION MULTIOBJECTIVE OPTIMIZATION OPTIMIZATION FOR RADIO RESOURCE MANAGEMENT EXAMPLES AND APPLICATIONS SPECTRAL EF?CIENCY FOR MULTIPLE INPUT MULTIPLE OUTPUT ULTRA-WIDEBAND COMMUNICATION SYSTEM WIDEBAND WAVEFORM DESIGN FOR SINGLE INPUT SINGLE OUTPUT COMMUNICATION SYSTEM WITH NONCOHERENT RECEIVER WIDEBAND WAVEFORM DESIGN FOR MULTIPLE INPUT SINGLE OUTPUT COGNITIVE RADIO WIDEBAND BEAMFORMING DESIGN LAYERING AS OPTIMIZATION DECOMPOSITION FOR COGNITIVE RADIO NETWORK SUMMARY MACHINE LEARNING UNSUPERVISED LEARNING CENTROID-BASED CLUSTERING K-NEAREST NEIGHBORS INDEPENDENT COMPONENT ANALYSIS NONNEGATIVE MATRIX FACTORIZATION SELF-ORGANIZING MAP SUPERVISED LEARNING LINEAR REGRESSION LOGISTIC REGRESSION ARTI?CIAL NEURAL NETWORK DECISION TREE LEARNING NAIVE BAYES CLASSI?ER SUPPORT VECTOR MACHINES SEMISUPERVISED LEARNING CONSTRAINED CLUSTERING CO-TRAINING GRAPH-BASED METHODS TRANSDUCTIVE INFERENCE TRANSFER LEARNING ACTIVE LEARNING REINFORCEMENT LEARNING Q-LEARNING MARKOV DECISION PROCESS PARTIALLY OBSERVABLE MDPS KERNEL-BASED LEARNING DIMENSIONALITY REDUCTION KERNEL PRINCIPAL COMPONENT ANALYSIS MULTIDIMENSIONAL SCALING ISOMAP LOCALLY-LINEAR EMBEDDING LAPLACIAN EIGENMAPS SEMIDE?NITE EMBEDDING ENSEMBLE LEARNING MARKOV CHAIN MONTE CARLO FILTERING TECHNIQUE KALMAN FILTERING PARTICLE FILTERING COLLABORATIVE FILTERING BAYESIAN NETWORK AGILE TRANSMISSION TECHNIQUES (I): MULTIPLE INPUT MULTIPLE OUTPUT BENE?TS OF MIMO ARRAY GAIN DIVERSITY GAIN MULTIPLEXING GAIN SPACE TIME CODING SPACE TIME BLOCK CODING SPACE TIME TRELLIS CODING LAYERED SPACE TIME CODING MULTI-USER MIMO SPACE-DIVISION MULTIPLE ACCESS MIMO BROADCAST CHANNEL MIMO MULTIPLE ACCESS CHANNEL MIMO INTERFERENCE CHANNEL MIMO NETWORK MIMO COGNITIVE RADIO NETWORK AGILE TRANSMISSION TECHNIQUES (II): ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING OFDM IMPLEMENTATION SYNCHRONIZATION CHANNEL ESTIMATION PEAK POWER PROBLEM ADAPTIVE TRANSMISSION SPECTRUM SHAPING ORTHOGONAL FREQUENCY DIVISION MULTIPLE ACCESS MIMO OFDM OFDM COGNITIVE RADIO NETWORK BASIC CONCEPTS OF GAMES ELEMENTS OF GAMES NASH EQUILIBRIUM: DE?NITION AND EXISTENCE NASH EQUILIBRIUM: COMPUTATION NASH EQUILIBRIUM: ZERO-SUM GAMES NASH EQUILIBRIUM: BAYESIAN CASE NASH EQUILIBRIUM: STOCHASTIC GAMES PRIMARY USER EMULATION ATTACK GAMES PUE ATTACK TWO-PLAYER CASE: A STRATEGIC-FORM GAME GAME IN QUEUING DYNAMICS: A STOCHASTIC GAME GAMES IN CHANNEL SYNCHRONIZATION BACKGROUND OF THE GAME GAME FORMULATION BAYESIAN EQUILIBRIUM NUMERICAL RESULTS GAMES IN COLLABORATIVE SPECTRUM SENSING FALSE REPORT ATTACK ELEMENTS OF GAME COGNITIVE RADIO NETWORK BASIC CONCEPTS OF NETWORKS NETWORK ARCHITECTURE NETWORK LAYERS CROSS-LAYER DESIGN MAIN CHALLENGES IN COGNITIVE RADIO NETWORKS COMPLEX NETWORKS CHANNEL ALLOCATION IN MAC LAYER PROBLEM FORMULATION SCHEDULING ALGORITHM SOLUTION DISCUSSION SCHEDULING IN MAC LAYER NETWORK MODEL GOAL OF SCHEDULING PERFORMANCE OF THE CNC ALGORITHM DISTRIBUTED SCHEDULING ALGORITHM ROUTING IN NETWORK LAYER CHALLENGES OF ROUTING IN COGNITIVE RADIO STATIONARY ROUTING DYNAMIC ROUTING CONGESTION CONTROL IN TRANSPORT LAYER CONGESTION CONTROL IN INTERNET CHALLENGES IN COGNITIVE RADIO TP-CRAHN EARLY START SCHEME COMPLEX NETWORKS IN COGNITIVE RADIO BRIEF INTRODUCTION TO COMPLEX NETWORKS CONNECTIVITY OF COGNITIVE RADIO NETWORKS BEHAVIOR PROPAGATION IN COGNITIVE RADIO NETWORKS COGNITIVE RADIO NETWORK AS SENSORS INTRUSION DETECTION BY MACHINE LEARNING JOINT SPECTRUM SENSING AND LOCALIZATION DISTRIBUTED ASPECT SYNTHETIC APERTURE RADAR WIRELESS TOMOGRAPHY MOBILE CROWDSENSING INTEGRATION OF 3S THE CYBER-PHYSICAL SYSTEM COMPUTING GRAPHICS PROCESSOR UNIT TASK DISTRIBUTION AND LOAD BALANCING SECURITY AND PRIVACY 12 10 SUMMARY