Wireless Communications

Giorgio M. Vitetta is a Full Professor of Telecommunications at the Department of Information Engineering of the University of Modena and Reggio Emilia. He received the Dr. Ing. Degree in Electronic Engineering (cum Laude) in 1990 and the Ph. D. degree in 1994, both from the University of Pisa, Italy.Desmond Taylor is the Tait Professor of Communications at the University of Canterbury. He gained his PhD in Electrical Engineering from McMaster University in Canada. He specializes in Digital Communication Systems. He is the director of journals for the IEEE Communications Society. Philippa Martin is a lecturer in Electrical Engineering at the University of Canterbury. Her research interests include coded modulation, error correction coding and decoding, reduced complexity decoding algorithms, iterative processing, space-time coding, detection and decoding, and combined equalization and decoding. Fabrizio Pancaldi received his Dr. Ing. Degree in Electronic Engineering (cum laude) and a Ph. D. degree in 2006, both from the University of Modena and Reggio Emilia, Italy. He is currently a Research Fellow and lectures in Telecommunication Networks.

• Preface xiList of Acronyms xiii1 Introduction 11.1 Structure of a Digital Communication System 31.2 Plan of the Book 71.3 Further Reading 8Part I MODULATION AND DETECTION2 Wireless Channels 112.1 Introduction 112.2 Mathematical Description of SISO Wireless Channels 162.2.1 Input–Output Characterization of a SISO Wireless Channel 162.2.2 Statistical Characterization of a SISO Wireless Channel 232.2.3 Reduced-Complexity Statistical Models for SISO Channels 362.3 Mathematical Description and Modeling of MIMO Wireless Channels 442.3.1 Input–Output Characterization of a MIMO Wireless Channel 452.3.2 Statistical Characterization of a MIMO Wireless Channel 502.3.3 Reduced-Complexity Statistical Modeling of MIMO Channels 572.4 Historical Notes 572.4.1 Large-Scale Fading Models 582.4.2 Small-Scale Fading Models 602.5 Further Reading 643 Digital Modulation Techniques 653.1 Introduction 653.2 General Structure of a Digital Modulator 653.3 Representation of Digital Modulated Waveforms on an Orthonormal Basis 683.4 Bandwidth of Digital Modulations 703.5 Passband PAM 743.5.1 Signal Model 743.5.2 Constellation Selection 763.5.3 Data Block Transmission with Passband PAM Signals for Frequency-Domain Equalization 793.5.4 Power Spectral Density of Linear Modulations 803.6 Continuous Phase Modulation 863.6.1 Signal Model 863.6.2 Full-Response CPM 893.6.3 Partial-Response CPM 933.6.4 Multi-h CPM 983.6.5 Alternative Representations of CPM Signals 1003.6.6 Data Block Transmission with CPM Signals for Frequency-Domain Equalization 1073.6.7 Power Spectral Density of Continuous Phase Modulations 1103.7 OFDM 1163.7.1 Introduction 1163.7.2 OFDM Signal Model 1223.7.3 Power Spectral Density of OFDM 1313.7.4 The PAPR Problem in OFDM 1353.8 Lattice-Based Multidimensional Modulations 1373.8.1 Lattices: Basic Definitions and Properties 1373.8.2 Elementary Constructions of Lattices 1443.9 Spectral Properties of a Digital Modulation at the Output of a Wireless Channel 1463.10 Historical Notes 1493.10.1 Passband PAM Signaling 1493.10.2 CPM Signaling 1513.10.3 MCM Signaling 1523.10.4 Power Spectral Density of Digital Modulations 1533.11 Further Reading 1544 Detection of Digital Signals over Wireless Channels: Decision Rules 1554.1 Introduction 1554.2 Wireless Digital Communication Systems: Modeling, Receiver Architecture and Discretization of the Received Signal 1564.2.1 General Model of a Wireless Communication System 1564.2.2 Receiver Architectures 1574.3 Optimum Detection in a Vector Communication System 1594.3.1 Description of a Vector Communication System 1594.3.2 Detection Strategies and Error Probabilities 1594.3.3 MAP and ML Detection Strategies 1624.3.4 Diversity Reception and Some Useful Theorems about Data Detection 1674.4 Mathematical Models for the Receiver Vector 1684.4.1 Extraction of a Set of Sufficient Statistics from the Received Signal 1694.4.2 Received Vector for PAM Signaling 1774.4.3 Received Vector for CPM Signaling 1814.4.4 Received Vector for OFDM Signaling 1844.5 Decision Strategies in the Presence of Channel Parameters: Optimal Metrics and Performance Bounds 1884.5.1 Signal Model and Algorithm Classification 1884.5.2 Detection for Transmission over of a Known Channel 1894.5.3 Detection in the Presence of a Statistically Known Channel 1984.5.4 Detection in the Presence of an Unknown Channel 2054.6 Expectation–Maximization Techniques for Data Detection 2074.6.1 The EM Algorithm 2074.6.2 The Bayesian EM Algorithm 2104.6.3 Initialization and Convergence of EM-Type Algorithms 2134.6.4 Other EM Techniques 2134.7 Historical Notes 2144.8 Further Reading 2165 Data-Aided Algorithms for Channel Estimation 2175.1 Channel Estimation Techniques 2185.1.1 Introduction 2185.1.2 Feedforward Estimation 2195.1.3 Recursive Estimation 2225.1.4 The Principle of Per-Survivor Processing 2275.2 Cram´er–Rao Bounds for Data-Aided Channel Estimation 2285.3 Data-Aided CIR Estimation Algorithms in PATs 2355.3.1 PAT Modeling and Optimization 2355.3.2 A Signal Processing Perspective on PAT Techniques 2385.4 Extensions to MIMO Channels 2445.4.1 Channel Estimation in SC MIMO PATs 2445.4.2 Channel Estimation in MC MIMO PATs 2455.5 Historical Notes 2455.6 Further Reading 2476 Detection of Digital Signals over Wireless Channels: Channel Equalization Algorithms 2496.1 Introduction 2496.2 Channel Equalization of Single-Carrier Modulations: Known CIR 2506.2.1 Channel Equalization in the Time Domain 2506.2.2 Channel Equalization in the Frequency Domain 2816.3 Channel Equalization of Multicarrier Modulations: Known CIR 2866.3.1 Optimal Detection in the Absence of IBI and ICI 2876.3.2 ICI Cancelation Techniques for Time-Varying Channels 2896.3.3 Equalization Strategies for IBI Compensation 2926.4 Channel Equalization of Single Carrier Modulations: Statistically Known CIR 2926.4.1 MLSD 2926.4.2 Other Equalization Strategies with Frequency-Flat Fading 2996.5 Channel Equalization of Multicarrier Modulations: Statistically Known CIR 3016.6 Joint Channel and Data Estimation: Single-Carrier Modulations 3026.6.1 Adaptive MLSD 3026.6.2 PSP MLSD 3036.6.3 Adaptive MAPBD/MAPSD 3056.6.4 Equalization Strategies Employing Reference-Based Channel Estimators with Frequency-Flat Fading 3066.7 Joint Channel and Data Estimation: Multicarrier Modulations 3076.7.1 Pilot-Based Equalization Techniques 3086.7.2 Semiblind Equalization Techniques 3106.8 Extensions to the MIMO Systems 3116.8.1 Equalization Techniques for Single-Carrier MIMO Communications 3116.8.2 Equalization Techniques for MIMO-OFDM Communications 3146.9 Historical Notes 3156.10 Further Reading 319Part II INFORMATION THEORY AND CODING SCHEMES7 Elements of Information Theory 3237.1 Introduction 3237.2 Capacity for Discrete Sources and Channels 3237.2.1 The Discrete Memoryless Channel 3247.2.2 The Continuous-Output Channel 3257.2.3 Channel Capacity 3267.3 Capacity of MIMO Fading Channels 3307.3.1 Frequency-Flat Fading Channel 3307.3.2 MIMO Channel Capacity 3327.3.3 Random Channel 3357.4 Historical Notes 3377.5 Further Reading 3388 An Introduction to Channel Coding Techniques 3398.1 Basic Principles 3398.2 Interleaving 3418.3 Taxonomy of Channel Codes 3438.4 Taxonomy of Coded Modulations 3448.5 Organization of the Following Chapters 3468.6 Historical Notes 3468.7 Further Reading 3479 Classical Coding Schemes 3499.1 Block Codes 3499.1.1 Introduction 3499.1.2 Structure of Linear Codes over GF(q) 3509.1.3 Properties of Linear Block Codes 3529.1.4 Cyclic Codes 3579.1.5 Other Relevant Linear Block Codes 3699.1.6 Decoding Techniques for Block Codes 3719.1.7 Error Performance 3889.2 Convolutional Codes 3909.2.1 Introduction 3909.2.2 Properties of Convolutional Codes 3949.2.3 Maximum Likelihood Decoding of Convolutional Codes 4089.2.4 MAP Decoding of Convolutional Codes 4139.2.5 Sequential Decoding of Convolutional Codes 4199.2.6 Error Performance of ML Decoding of Convolutional Codes 4229.3 Classical Concatenated Coding 4329.3.1 Parallel Concatenation: Product Codes 4329.3.2 Serial Concatenation: Outer RS Code 4349.4 Historical Notes 4359.4.1 Algebraic Coding 4359.4.2 Probabilistic Coding 4389.5 Further Reading 43910 Modern Coding Schemes 44110.1 Introduction 44110.2 Concatenated Convolutional Codes 44210.2.1 Parallel Concatenated Coding Schemes 44210.2.2 Serially Concatenated Coding Schemes 44410.2.3 Hybrid Concatenated Coding Schemes 44510.3 Concatenated Block Codes 44510.4 Other Modern Concatenated Coding Schemes 44610.4.1 Repeat and Accumulate Codes 44610.4.2 Serial Concatenation of Coding Schemes and Differential Modulations 44710.5 Iterative Decoding Techniques for Concatenated Codes 44810.5.1 The Turbo Principle 44810.5.2 SiSo Decoding Algorithms 45510.5.3 Applications 45910.5.4 Performance Bounds 46510.6 Low-Density Parity Check Codes 46810.6.1 Definition and Classification 46810.6.2 Graphic Representation of LDPC Codes via Tanner Graphs 46810.6.3 Minimum Distance and Weight Spectrum 47110.6.4 LDPC Code Design Approaches 47210.6.5 Efficient Algorithms for LDPC Encoding 47710.7 Decoding Techniques for LDPC Codes 47810.7.1 Introduction to Decoding via Message Passing Algorithms 47810.7.2 SPA and MSA 48110.7.3 Technical Issues on LDPC Decoding via MP 48910.8 Codes on Graphs 49410.9 Historical Notes 50110.10 Further Reading 50311 Signal Space Codes 50511.1 Introduction 50511.2 Trellis Coding with Expanded Signal Sets 50511.2.1 Code Construction 50611.2.2 Decoding Algorithms 51711.2.3 Error Performance 51811.3 Bit-Interleaved Coded Modulation 52011.3.1 Code Construction 52011.3.2 Decoding Algorithms 52111.3.3 Error Performance 52211.4 Modulation Codes Based on Multilevel Coding 52411.4.1 Code Construction for AWGN Channels 52411.4.2 Multistage Decoder 52811.4.3 Error Performance 52911.4.4 Multilevel Codes for Rayleigh Flat Fading Channels 53011.5 Space-Time Coding 53111.5.1 ST Coding for Frequency-Flat Fading Channels 53111.5.2 ST Coding for Frequency-Selective Fading Channels 56111.6 Historical Notes 56511.7 Further Reading 56612 Combined Equalization and Decoding 56712.1 Introduction 56712.2 Noniterative Techniques 56812.3 Algorithms for Combined Equalization and Decoding 57112.3.1 Introduction 57112.3.2 Turbo Equalization from a FG Perspective 57512.3.3 Reduced-Complexity Techniques for SiSo Equalization 58012.3.4 Turbo Equalization in the FD 58312.3.5 Turbo Equalization in the Presence of an Unknown Channel 58512.4 Extension to MIMO 58612.5 Historical Notes 58812.5.1 Reduced-Complexity SiSo Equalization 58812.5.2 Error Performance and Convergence Speed in Turbo Equalization 58812.5.3 SiSo Equalization Algorithms in the Frequency Domain 58912.5.4 Use of Precoding 58912.5.5 Turbo Equalization and Factor Graphs 58912.5.6 Turbo Equalization for MIMO Systems 58912.5.7 Related Techniques 59012.6 Further Reading 590Appendix A Fourier Transforms 591Appendix B Power Spectral Density of Random Processes 593B.1 Power Spectral Density of a Wide-Sense Stationary Random Process 593B.2 Power Spectral Density of a Wide-Sense Cyclostationary Random Process 594B.3 Power Spectral Density of a Bandpass Random Process 595Appendix C Matrix Theory 597Appendix D Signal Spaces 601D.1 Representation of Deterministic Signals 601D.1.1 Basic Definitions 601D.1.2 Representation of Deterministic Signals via Orthonormal Bases 602D.2 Representation of Random Signals via Orthonormal Bases 606Appendix E Groups, Finite Fields and Vector Spaces 609E.1 Groups 609E.2 Fields 611E.2.1 Axiomatic Definition of a Field and Finite Fields 611E.2.2 Polynomials and Extension Fields 612E.2.3 Other Definitions and Properties 616E.2.4 Computation Techniques for Finite Fields 620E.3 Vector Spaces 622Appendix F Error Function and Related Functions 625References 629Index 713