Wireless communications : algorithmic techniques

Title:

Publication Information:

ENK, : Wiley, 2013.

Physical Description:

xix, 724 p. : ill. ; 26 cm.

ISBN:

9780470512395

Subject Term:

Wireless communication systems -- Mathematics

Algebra

Added Author:

Vitetta, Giorgio

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Library	Item Barcode	Call Number	Material Type	Item Category 1	Status
Searching... PSZ JB	30000010323157	TK5102.83 W574 2013	Open Access Book	Book	Searching... Unknown

This book introduces the theoretical elements at the basis of various classes of algorithms commonly employed in the physical layer (and, in part, in MAC layer) of wireless communications systems. It focuses on single user systems, so ignoring multiple access techniques. Moreover, emphasis is put on single-input single-output (SISO) systems, although some relevant topics about multiple-input multiple-output (MIMO) systems are also illustrated. Comprehensive wireless specific guide to algorithmic techniques Provides a detailed analysis of channel equalization and channel coding for wireless applications Unique conceptual approach focusing in single user systems Covers algebraic decoding, modulation techniques, channel coding and channel equalisation

Author Notes

Giorgio M. Vitetta, University of Modena and Reggio Emilia, Italy
Desmond P. Taylor, University of Canterbury, Christchurch, New Zealand
Giulio Colavolpe, University of Parma, Italy
Fabrizio Pancaldi, University of Modena and Reggio Emilia, Italy
Philippa A. Martin, University of Canterbury, Christchurch, New Zealand

Preface	p. xi
List of Acronyms	p. xiii
1 Introduction	p. 1
1.1 Structure of a Digital Communication System	p. 3
1.2 Plan of the Book	p. 7
1.3 Further Reading	p. 8
Part I Modulation and Detection
2 Wireless Channels	p. 11
2.1 Introduction	p. 11
2.2 Mathematical Description of SISO Wireless Channels	p. 16
2.2.1 Input-Output Characterization of a SISO Wireless Channel	p. 16
2.2.2 Statistical Characterization of a SISO Wireless Channel	p. 23
2.2.3 Reduced-Complexity Statistical Models for SISO Channels	p. 36
2.3 Mathematical Description and Modeling of MTMO Wireless Channels	p. 44
2.3.1 Input-Output Characterization of a MIMO Wireless Channel	p. 45
2.3.2 Statistical Characterization of a MIMO Wireless Channel	p. 50
2.3.3 Reduced-Complexity Statistical Modeling of MIMO Channels	p. 57
2.4 Historical Notes	p. 57
2.4.1 Large-Scale Fading Models	p. 58
2.4.2 Small-Scale Fading Models	p. 60
2.5 Further Reading	p. 64
3 Digital Modulation Techniques	p. 65
3.1 Introduction	p. 65
3.2 General Structure of a Digital Modulator	p. 65
3.3 Representation of Digital Modulated Waveforms on an Orthonormal Basis	p. 68
3.4 Bandwidth of Digital Modulations	p. 70
3.5 Passband PAM	p. 74
3.5.1 Signal Model	p. 74
3.5.2 Constellation Selection	p. 76
3.5.3 Data Block Transmission with Passband PAM Signals for Frequency-Domain Equalization	p. 79
3.5.4 Power Spectral Density of Linear Modulations	p. 80
3.6 Continuous Phase Modulation	p. 86
3.6.1 Signal Model	p. 86
3.6.2 Full-Response CPM	p. 89
3.6.3 Partial-Response CPM	p. 93
3.6.4 Multi-h CPM	p. 98
3.6.5 Alternative Representations of CPM Signals	p. 100
3.6.6 Data Block Transmission with CPM Signals for Frequency-Domain Equalization	p. 107
3.6.7 Power Spectral Density of Continuous Phase Modulations	p. 110
3.7 OFDM	p. 116
3.7.1 Introduction	p. 116
3.7.2 OFDM Signal Model	p. 122
3.7.3 Power Spectral Density of OFDM	p. 131
3.7.4 The PAPR Problem in OFDM	p. 135
3.8 Lattice-Based Multidimensional Modulations	p. 137
3.8.1 Lattices: Basic Definitions and Properties	p. 137
3.8.2 Elementary Constructions of Lattices	p. 144
3.9 Spectral Properties of a Digital Modulation at the Output of a Wireless Channel	p. 146
3.10 Historical Notes	p. 149
3.10.1 Passband PAM Signaling	p. 149
3.10.2 CPM Signaling	p. 151
3.10.3 MCM Signaling	p. 152
3.10.4 Power Spectral Density of Digital Modulations	p. 153
3.11 Further Reading	p. 154
4 Detection of Digital Signals over Wireless Channels: Decision Rules	p. 155
4.1 Introduction	p. 155
4.2 Wireless Digital Communication Systems: Modeling, Receiver Architecture and Discretization of the Received Signal	p. 156
4.2.1 General Model of a Wireless Communication System	p. 156
4.2.2 Receiver Architectures	p. 157
4.3 Optimum Detection in a Vector Communication System	p. 159
4.3.1 Description of a Vector Communication System	p. 159
4.3.2 Detection Strategies and Error Probabilities	p. 159
4.3.3 MAP and ML Detection Strategies	p. 162
4.3.4 Diversity Reception and Some Useful Theorems about Data Detection	p. 167
4.4 Mathematical Models for the Receiver Vector	p. 168
4.4.1 Extraction of a Set of Sufficient Statistics from the Received Signal	p. 169
4.4.2 Received Vector for PAM Signaling	p. 177
4.4.3 Received Vector for CPM Signaling	p. 181
4.4.4 Received Vector for OFDM Signaling	p. 184
4.5 Decision Strategies in the Presence of Channel Parameters: Optimal Metrics and Performance Bounds	p. 188
4.5.1 Signal Model and Algorithm Classification	p. 188
4.5.2 Detection for Transmission over of a Known Channel	p. 189
4.5.3 Detection in the Presence of a Statistically Known Channel	p. 198
4.5.4 Detection in the Presence of an Unknown Channel	p. 205
4.6 Expectation-Maximization Techniques for Data Detection	p. 207
4.6.1 The EM Algorithm	p. 207
4.6.2 The Bayesian EM Algorithm	p. 210
4.6.3 Initialization and Convergence of EM-Type Algorithms	p. 213
4.6.4 Other EM Techniques	p. 213
4.7 Historical Notes	p. 214
4.8 Further Reading	p. 216
5 Data-Aided Algorithms for Channel Estimation	p. 217
5.1 Channel Estimation Techniques	p. 218
5.1.1 Introduction	p. 218
5.1.2 Feedforward Estimation	p. 219
5.1.3 Recursive Estimation	p. 222
5.1.4 The Principle of Per-Survivor Processing	p. 227
5.2 Cramér-Rao Bounds for Data-Aided Channel Estimation	p. 228
5.3 Data-Aided CIR Estimation Algorithms in PATs	p. 235
5.3.1 PAT Modeling and Optimization	p. 235
5.3.2 A Signal Processing Perspective on PAT Techniques	p. 238
5.4 Extensions to MTMO Channels	p. 244
5.4.1 Channel Estimation in SC MIMO PATs	p. 244
5.4.2 Channel Estimation in MC MIMO PATs	p. 245
5.5 Historical Notes	p. 245
5.6 Further Reading	p. 247
6 Detection of Digital Signals over Wireless Channels: Channel Equalization Algorithms	p. 249
6.1 Introduction	p. 249
6.2 Channel Equalization of Single-Carrier Modulations: Known CIR	p. 250
6.2.1 Channel Equalization in the Time Domain	p. 250
6.2.2 Channel Equalization in the Frequency Domain	p. 281
6.3 Channel Equalization of Multicarrier Modulations: Known CIR	p. 286
6.3.1 Optimal Detection in the Absence of IBI and ICI	p. 287
6.3.2 ICI Cancelation Techniques for Time-Varying Channels	p. 289
6.3.3 Equalization Strategies for IBI Compensation	p. 292
6.4 Channel Equalization of Single Carrier Modulations: Statistically Known CIR	p. 292
6.4.1 MLSD	p. 292
6.4.2 Other Equalization Strategies with Frequency-Flat Fading	p. 299
6.5 Channel Equalization of Multicarrier Modulations: Statistically Known CIR	p. 301
6.6 Joint Channel and Data Estimation: Single-Carrier Modulations	p. 302
6.6.1 Adaptive MLSD	p. 302
6.6.2 PSPMLSD	p. 303
6.6.3 Adaptive MAPBD/MAPSD	p. 305
6.6.4 Equalization Strategies Employing Reference-Based Channel Estimators with Frequency-Flat Fading	p. 306
6.7 Joint Channel and Data Estimation: Multicarrier Modulations	p. 307
6.7.1 Pilot-Based Equalization Techniques	p. 308
6.7.2 Semiblind Equalization Techniques	p. 310
6.8 Extensions to the MTMO Systems	p. 311
6.8.1 Equalization Techniques for Single-Carrier MIMO Communications	p. 311
6.8.2 Equalization Techniques for MIMO-OFDM Communications	p. 314
6.9 Historical Notes	p. 315
6.10 Further Reading	p. 319
Part II Information Theory and Coding Schemes
7 Elements of Information Theory	p. 323
7.1 Introduction	p. 323
7.2 Capacity for Discrete Sources and Channels	p. 323
7.2.1 The Discrete Memoryless Channel	p. 324
7.2.2 The Continuous-Output Channel	p. 325
7.2.3 Channel Capacity	p. 326
7.3 Capacity of MIMO Fading Channels	p. 330
7.3.1 Frequency-Flat Fading Channel	p. 330
7.3.2 MIMO Channel Capacity	p. 332
7.3.3 Random Channel	p. 335
7.4 Historical Notes	p. 337
7.5 Further Reading	p. 338
8 An Introduction to Channel Coding Techniques	p. 339
8.1 Basic Principles	p. 339
8.2 Interleaving	p. 341
8.3 Taxonomy of Channel Codes	p. 343
8.4 Taxonomy of Coded Modulations	p. 344
8.5 Organization of the Following Chapters	p. 346
8.6 Historical Notes	p. 346
8.7 Further Reading	p. 347
9 Classical Coding Schemes	p. 349
9.1 Block Codes	p. 349
9.1.1 Introduction	p. 349
9.1.2 Structure of Linear Codes over GF(q)	p. 350
9.1.3 Properties of Linear Block Codes	p. 352
9.1.4 Cyclic Codes	p. 357
9.1.5 Other Relevant Linear Block Codes	p. 369
9.1.6 Decoding Techniques for Block Codes	p. 371
9.1.7 Error Performance	p. 388
9.2 Convolutional Codes	p. 390
9.2.1 Introduction	p. 390
9.2.2 Properties of Convolutional Codes	p. 394
9.2.3 Maximum Likelihood Decoding of Convolutional Codes	p. 408
9.2.4 MAP Decoding of Convolutional Codes	p. 413
9.2.5 Sequential Decoding of Convolutional Codes	p. 419
9.2.6 Error Performance of ML Decoding of Convolutional Codes	p. 422
9.3 Classical Concatenated Coding	p. 432
9.3.1 Parallel Concatenation: Product Codes	p. 432
9.3.2 Serial Concatenation: Outer RS Code	p. 434
9.4 Historical Notes	p. 435
9.4.1 Algebraic Coding	p. 435
9.4.2 Probabilistic Coding	p. 438
9.5 Further Reading	p. 439
10 Modern Coding Schemes	p. 441
10.1 Introduction	p. 441
10.2 Concatenated Convolutional Codes	p. 442
10.2.1 Parallel Concatenated Coding Schemes	p. 442
10.2.2 Serially Concatenated Coding Schemes	p. 444
10.2.3 Hybrid Concatenated Coding Schemes	p. 445
10.3 Concatenated Block Codes	p. 445
10.4 Other Modern Concatenated Coding Schemes	p. 446
10.4.1 Repeat and Accumulate Codes	p. 446
10.4.2 Serial Concatenation of Coding Schemes and Differential Modulations	p. 447
10.5 Iterative Decoding Techniques for Concatenated Codes	p. 448
10.5.1 The Turbo Principle	p. 448
10.5.2 SiSo Decoding Algorithms	p. 455
10.5.3 Applications	p. 459
10.5.4 Performance Bounds	p. 465
10.6 Low-Density Parity Check Codes	p. 468
10.6.1 Definition and Classification	p. 468
10.6.2 Graphic Representation of LDPC Codes via Tanner Graphs	p. 468
10.6.3 Minimum Distance and Weight Spectrum	p. 471
10.6.4 LDPC Code Design Approaches	p. 472
10.6.5 Efficient Algorithms for LDPC Encoding	p. 477
10.7 Decoding Techniques for LDPC Codes	p. 478
10.7.1 Introduction to Decoding via Message Passing Algorithms	p. 478
10.7.2 SPA and MSA	p. 481
10.7.3 Technical Issues on LDPC Decoding via MP	p. 489
10.8 Codes on Graphs	p. 494
10.9 Historical Notes	p. 501
10.10 Further Reading	p. 503
11 Signal Space Codes	p. 505
11.1 Introduction	p. 505
11.2 Trellis Coding with Expanded Signal Sets	p. 505
11.2.1 Code Construction	p. 506
11.2.2 Decoding Algorithms	p. 517
11.2.3 Error Performance	p. 518
11.3 Bit-Interleaved Coded Modulation	p. 520
11.3.1 Code Construction	p. 520
11.3.2 Decoding Algorithms	p. 521
11.3.3 Error Performance	p. 522
11.4 Modulation Codes Based on Multilevel Coding	p. 524
11.4.1 Code Construction for AWGN Channels	p. 524
11.4.2 Multistage Decoder	p. 528
11.4.3 Error Performance	p. 529
11.4.4 Multilevel Codes for Rayleigh Flat Fading Channels	p. 530
11.5 Space-Time Coding	p. 531
11.5.1 ST Coding for Frequency-Flat Fading Channels	p. 531
11.5.2 ST Coding for Frequency-Selective Fading Channels	p. 561
11.6 Historical Notes	p. 565
11.7 Further Reading	p. 566
12 Combined Equalization and Decoding	p. 567
12.1 Introduction	p. 567
12.2 Noniterative Techniques	p. 568
12.3 Algorithms for Combined Equalization and Decoding	p. 571
12.3.1 Introduction	p. 571
12.3.2 Turbo Equalization from a FG Perspective	p. 575
12.3.3 Reduced-Complexity Techniques for SiSo Equalization	p. 580
12.3.4 Turbo Equalization in the FD	p. 583
12.3.5 Turbo Equalization in the Presence of an Unknown Channel	p. 585
12.4 Extension to MTMO	p. 586
12.5 Historical Notes	p. 588
12.5.1 Reduced-Complexity SiSo Equalization	p. 588
12.5.2 Error Performance and Convergence Speed in Turbo Equalization	p. 588
12.5.3 SiSo Equalization Algorithms in the Frequency Domain	p. 589
12.5.4 Use of Precoding	p. 589
12.5.5 Turbo Equalization and Factor Graphs	p. 589
12.5.6 Turbo Equalization for MIMO Systems	p. 589
12.5.7 Related Techniques	p. 590
12.6 Further Reading	p. 590
Appendix A Fourier Transforms	p. 591
Appendix B Power Spectral Density of Random Processes	p. 593
B.1 Power Spectral Density of a Wide-Sense Stationary Random Process	p. 593
B.2 Power Spectral Density of a Wide-Sense Cyclostationary Random Process	p. 594
B.3 Power Spectral Density of a Bandpass Random Process	p. 595
Appendix C Matrix Theory	p. 597
Appendix D Signal Spaces	p. 601
D.1 Representation of Deterministic Signals	p. 601
D.1.1 Basic Definitions	p. 601
D.1.2 Representation of Deterministic Signals via Orthonormal Bases	p. 602
D.2 Representation of Random Signals via Orthonormal Bases	p. 606
Appendix E Groups, Finite Fields and Vector Spaces	p. 609
E.1 Groups	p. 609
E.2 Fields	p. 611
E.2.1 Axiomatic Definition of a Field and Finite Fields	p. 611
E.2.2 Polynomials and Extension Fields	p. 612
E.2.3 Other Definitions and Properties	p. 616
E.2.4 Computation Techniques for Finite Fields	p. 620
E.3 Vector Spaces	p. 622
Appendix F Error Function and Related Functions	p. 625
References	p. 629
Index	p. 713

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