Coordinated Multiuser Communications / Edition 1

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Overview

Coordinated Multiuser Communications provides for the first time a unified treatment of multiuser detection and multiuser decoding in a single volume.
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Product Details

  • ISBN-13: 9781402040740
  • Publisher: Springer Netherlands
  • Publication date: 5/5/2006
  • Edition description: 2006
  • Edition number: 1
  • Pages: 270
  • Product dimensions: 9.21 (w) x 6.14 (h) x 0.69 (d)

Table of Contents

List of Figures xi

List of Tables xvii

Preface xix

1 Introduction 1

1.1 The Dawn of Digital Communications 1

1.2 Multiple Terminal Networks 3

1.3 Multiple-Access Channel 6

1.4 Degrees of Coordination 7

1.4.1 Transmitter and Receiver Cooperation 7

1.4.2 Synchronization 9

1.4.3 Fixed Allocation Schemes 9

1.5 Network vs. Signal Processing Complexity 10

1.6 Future Directions 11

2 Linear Multiple-Access 13

2.1 Continuous Time Model 14

2.2 Discrete Time Model 17

2.3 Matrix-Algebraic Representation 18

2.4 Symbol Synchronous Model 21

2.5 Principles of Detection 22

2.5.1 Sufficient Statistics and Matched Filters 24

2.5.2 The Correlation Matrix 25

2.5.3 Single-User Matched Filter Detector 27

2.5.4 Optimal Detection 29

2.5.5 Individually Optimal Detection 30

2.6 Access Strategies 31

2.6.1 Time and Frequency Division Multiple-Access 31

2.6.2 Direct-Sequence Code Division Multiple Access 32

2.6.3 Narrow Band Multiple-Access 36

2.6.4 Multiple Antenna Channels 37

2.6.5 Cellular Networks 39

2.6.6 Satellite Spot-Beams Channels 41

2.7 Sequence Design 42

2.7.1 Orthogonal and Unitary Sequences 42

2.7.2 Hadamard Sequences 43

3 Multiuser Information Theory 45

3.1 Introduction 45

3.2 The Multiple-Access Channel 46

3.2.1 Probabilistic Channel Model 46

3.2.2 The Capacity Region 48

3.3 Binary-Input Channels 54

3.3.1 Binary Adder Channel 54

3.3.2 Binary Multiplier Channel 59

3.4 Gaussian Multiple-Access Channels 59

3.4.1 Scalar Gaussian Multiple-Access Channel 59

3.4.2 Code-Division Multiple-Access 63

3.5 Multiple-Access Codes 73

3.5.1 Block Codes 75

3.5.2 Convolutional and Trellis Codes 81

3.6 Superposition and Layering81

3.7 Feedback 84

3.8 Asynchronous Channels 90

4 Multiuser Detection 97

4.1 Introduction 97

4.2 Optimal Detection 100

4.2.1 Jointly Optimal Detection 100

4.2.2 Individually Optimal Detection: APP Detection 107

4.2.3 Performance Bounds - The Minimum Distance 109

4.3 Sub-Exponential Complexity Signature Sequences 112

4.4 Signal Layering 115

4.4.1 Correlation Detection - Matched Filtering 118

4.4.2 Decorrelation 119

4.4.3 Error Probabilities and Geometry 120

4.4.4 The Decorrelator with Random Spreading Codes 122

4.4.5 Minimum-Mean Square Error (MMSE) Filter 124

4.4.6 Error Performance of the MMSE 126

4.4.7 The MMSE Receiver with Random Spreading Codes 127

4.4.8 Whitening Filters 128

4.4.9 Whitening Filter for the Asynchronous Channel 132

4.5 Different Received Power Levels 134

4.5.1 The Matched Filter Detector 134

4.5.2 The MMSE Filter Detector 135

5 Implementation of Multiuser Detectors 139

5.1 Iterative Filter Implementation 139

5.1.1 Multistage Receivers 139

5.1.2 Iterative Matrix Solution Methods 142

5.1.3 Jacobi Iteration and Parallel Cancellation Methods 143

5.1.4 Stationary Iterative Methods 147

5.1.5 Successive Relaxation and Serial Cancellation Methods 148

5.1.6 Performance of Iterative Multistage Filters 151

5.2 Approximate Maximum Likelihood 158

5.2.1 Monotonic Metrics via the QR-Decomposition 159

5.2.2 Tree-Search Methods 161

5.2.3 Lattice Methods 164

5.3 Approximate APP Computation 170

5.4 List Sphere Detector 171

5.4.1 Modified Geometry List Sphere Detector 172

5.4.2 Other Approaches 172

6 Joint Multiuser Decoding 175

6.1 Introduction 175

6.2 Single-User Decoding 179

6.2.1 The Projection Receiver (PR) 179

6.2.2 PR Receiver Geometry and Metric Generation 182

6.2.3 Performance of the Projection Receiver 185

6.3 Iterative Decoding 192

6.3.1 Signal Cancellation 194

6.3.2 Convergence - Variance Transfer Analysis 195

6.3.3 Simple FEC Codes - Good Codeword Estimators 202

6.4 Filters in the Loop 209

6.4.1 Per-User MMSE Filters 209

6.4.2 Low-Complexity Iterative Loop Filters 214

6.4.3 Examples and Comparisons 217

6.5 Asymmetric Operating Conditions 219

6.5.1 Unequal Received Power Levels 220

6.5.2 Optimal Power Profiles 222

6.5.3 Unequal Rate Distributions 228

6.5.4 Finite Numbers of Power Groups 232

6.6 Proof of Lemma 6.7 234

A Estimation and Detection 237

A.1 Bayesian Estimation and Detection 237

A.2 Sufficiency 239

A.3 Linear Cost 241

A.4 Quadratic Cost 242

A.4.1 Minimum Mean Squared Error 242

A.4.2 Cramer-Rao Inequality 243

A.4.3 Jointly Gaussian Model 244

A.4.4 Linear MMSE Estimation 245

A.5 Hamming Cost 245

A.5.1 Minimum probability of Error 246

A.5.2 Relation to the MMSE Estimator 246

A.5.3 Maximum Likelihood Estimation 246

References 249

Author Index 261

Subject Index 265

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