Mimo-Ofdm Wireless Communications with MATLAB

1. Auflage 2010
ISBN: 978-0-470-82561-7
Verlag: Wiley

Buch, Englisch, 544 Seiten, Format (B × H): 183 mm x 260 mm, Gewicht: 1048 g

Reihe: Wiley - IEEE

MIMO-OFDM is a key technology for next-generation cellular communications (3GPP-LTE, Mobile WiMAX, IMT-Advanced) as well as wireless LAN (IEEE 802.11a, IEEE 802.11n), wireless PAN (MB-OFDM), and broadcasting (DAB, DVB, DMB). In MIMO-OFDM Wireless Communications with MATLAB, the authors provide a comprehensive introduction to the theory and practice of wireless channel modeling, OFDM, and MIMO, using MATLAB programs to simulate the various techniques on MIMO-OFDM systems.
- One of the only books in the area dedicated to explaining simulation aspects
- Covers implementation to help cement the key concepts
- Uses materials that have been classroom-tested in numerous universities
- Provides the analytic solutions and practical examples with downloadable MATLAB codes
- Simulation examples based on actual industry and research projects
- Presentation slides with key equations and figures for instructor use

MIMO-OFDM Wireless Communications with MATLAB is a key text for graduate students in wireless communications. Professionals and technicians in wireless communication fields, graduate students in signal processing, as well as senior undergraduates majoring in wireless communications will find this book a practical introduction to the MIMO-OFDM techniques.

Instructor materials and MATLAB code examples available for download at www.wiley.com/go/chomimo

Autoren/Hrsg.

Cho, Yong Soo

Kim, Jaekwon

Yang, Won Y

Yang, Won Young

Kang, Chung G

Kang, Chung-Gu

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Drahtlostechnologie

Inhaltsverzeichnis

Preface xiii

Limits of Liability and Disclaimer of Warranty of Software xv

1 The Wireless Channel: Propagation and Fading 1

1.1 Large-Scale Fading 4

1.1.1 General Path Loss Model 4

1.1.2 Okumura/Hata Model 8

1.1.3 IEEE 802.16d Model 10

1.2 Small-Scale Fading 15

1.2.1 Parameters for Small-Scale Fading 15

1.2.2 Time-Dispersive vs. Frequency-Dispersive Fading 16

1.2.3 Statistical Characterization and Generation of Fading Channel 19

2 SISO Channel Models 25

2.1 Indoor Channel Models 25

2.1.1 General Indoor Channel Models 26

2.1.2 IEEE 802.11 Channel Model 28

2.1.3 Saleh-Valenzuela (S-V) Channel Model 30

2.1.4 UWB Channel Model 35

2.2 Outdoor Channel Models 40

2.2.1 FWGN Model 41

2.2.2 Jakes Model 50

2.2.3 Ray-Based Channel Model 54

2.2.4 Frequency-Selective Fading Channel Model 61

2.2.5 SUI Channel Model 65

3 MIMO Channel Models 71

3.1 Statistical MIMO Model 71

3.1.1 Spatial Correlation 73

3.1.2 PAS Model 76

3.2 I-METRA MIMO Channel Model 84

3.2.1 Statistical Model of Correlated MIMO Fading Channel 84

3.2.2 Generation of Correlated MIMO Channel Coefficients 88

3.2.3 I-METRA MIMO Channel Model 90

3.2.4 3GPP MIMO Channel Model 94

3.3 SCM MIMO Channel Model 97

3.3.1 SCM Link-Level Channel Parameters 98

3.3.2 SCM Link-Level Channel Modeling 102

3.3.3 Spatial Correlation of Ray-Based Channel Model 105

4 Introduction to OFDM 111

4.1 Single-Carrier vs. Multi-Carrier Transmission 111

4.1.1 Single-Carrier Transmission 111

4.1.2 Multi-Carrier Transmission 115

4.1.3 Single-Carrier vs. Multi-Carrier Transmission 120

4.2 Basic Principle of OFDM 121

4.2.1 OFDM Modulation and Demodulation 121

4.2.2 OFDM Guard Interval 126

4.2.3 OFDM Guard Band 132

4.2.4 BER of OFDM Scheme 136

4.2.5 Water-Filling Algorithm for Frequency-Domain Link Adaptation 139

4.3 Coded OFDM 142

4.4 OFDMA: Multiple Access Extensions of OFDM 143

4.4.1 Resource Allocation – Subchannel Allocation Types 145

4.4.2 Resource Allocation – Subchannelization 146

4.5 Duplexing 150

5 Synchronization for OFDM 153

5.1 Effect of STO 153

5.2 Effect of CFO 156

5.2.1 Effect of Integer Carrier Frequency Offset (IFO) 159

5.2.2 Effect of Fractional Carrier Frequency Offset (FFO) 160

5.3 Estimation Techniques for STO 162

5.3.1 Time-Domain Estimation Techniques for STO 162

5.3.2 Frequency-Domain Estimation Techniques for STO 168

5.4 Estimation Techniques for CFO 170

5.4.1 Time-Domain Estimation Techniques for CFO 170

5.4.2 Frequency-Domain Estimation Techniques for CFO 173

5.5 Effect of Sampling Clock Offset 177

5.5.1 Effect of Phase Offset in Sampling Clocks 177

5.5.2 Effect of Frequency Offset in Sampling Clocks 178

5.6 Compensation for Sampling Clock Offset 178

5.7 Synchronization in Cellular Systems 180

5.7.1 Downlink Synchronization 180

5.7.2 Uplink Synchronization 183

6 Channel Estimation 187

6.1 Pilot Structure 187

6.1.1 Block Type 187

6.1.2 Comb Type 188

6.1.3 Lattice Type 189

6.2 Training Symbol-Based Channel Estimation 190

6.2.1 LS Channel Estimation 190

6.2.2 MMSE Channel Estimation 191

6.3 DFT-Based Channel Estimation 195

6.4 Decision-Directed Channel Estimation 199

6.5 Advanced Channel Estimation Techniques 199

6.5.1 Channel Estimation Using a Superimposed Signal 199

6.5.2 Channel Estimation in Fast Time-Varying Channels 201

6.5.3 EM Algorithm-Based Channel Estimation 204

6.5.4 Blind Channel Estimation 206

7 PAPR Reduction 209

7.1 Introduction to PAPR 209

7.1.1 Definition of PAPR 210

7.1.2 Distribution of OFDM Signal 216

7.1.3 PAPR and Oversampling 218

7.1.4 Clipping and SQNR 222

7.2 PAPR Reduction Techniques 224

7.2.1 Clipping and Filtering 224

7.2.2 PAPR Reduction Code 231

7.2.3 Selective Mapping 233

7.2.4 Partial Transmit Sequence 234

7.2.5 Tone Reservation 238

7.2.6 Tone Injection 239

7.2.7 DFT Spreading 241

8 Inter-Cell Interference Mitigation Techniques 251

8.1 Inter-Cell Interference Coordination Technique 251

8.1.1 Fractional Frequency Reuse 251

8.1.2 Soft Frequency Reuse 254

8.1.3 Flexible Fractional Frequency Reuse 255

8.1.4 Dynamic Channel Allocation 256

8.2 Inter-Cell Interference Randomization Technique 257

8.2.1 Cell-Specific Scrambling 257

8.2.2 Cell-Specific Interleaving 258

8.2.3 Frequency-Hopping OFDMA 258

8.2.4 Random Subcarrier Allocation 260

8.3 Inter-Cell Interference Cancellation Technique 260

8.3.1 Interference Rejection Combining Technique 260

8.3.2 IDMA Multiuser Detection 262

9 MIMO: Channel Capacity 263

9.1 Useful Matrix Theory 263

9.2 Deterministic MIMO Channel Capacity 265

9.2.1 Channel Capacity when CSI is Known to the Transmitter Side 266

9.2.2 Channel Capacity when CSI is Not Available at the Transmitter Side 270

9.2.3 Channel Capacity of SIMO and MISO Channels 271

9.3 Channel Capacity of Random MIMO Channels 272

10 Antenna Diversity and Space-Time Coding Techniques 281

10.1 Antenna Diversity 281

10.1.1 Receive Diversity 283

10.1.2 Transmit Diversity 287

10.2 Space-Time Coding (STC): Overview 287

10.2.1 System Model 287

10.2.2 Pairwise Error Probability 289

10.2.3 Space-Time Code Design 292

10.3 Space-Time Block Code (STBC) 294

10.3.1 Alamouti Space-Time Code 294

10.3.2 Generalization of Space-Time Block Coding 298

10.3.3 Decoding for Space-Time Block Codes 302

10.4 Space-Time Trellis Code 307

10.4.1 Space-Time Trellis Encoder 307

10.4.2 Space-Time Trellis Code: Illustrative Example 310

11 Signal Detection for Spatially Multiplexed MIMO Systems 319

11.1 Linear Signal Detection 319

11.1.1 ZF Signal Detection 320

11.1.2 MMSE Signal Detection 321

11.2 OSIC Signal Detection 322

11.3 ML Signal Detection 327

11.4 Sphere Decoding Method 329

11.5 QRM-MLD Method 339

11.6 Lattice Reduction-Aided Detection 344

11.6.1 Lenstra-Lenstra-Lovasz (LLL) Algorithm 345

11.6.2 Application of Lattice Reduction 349

11.7 Soft Decision for MIMO Systems 352

11.7.1 Log-Likelihood-Ratio (LLR) for SISO Systems 353

11.7.2 LLR for Linear Detector-Based MIMO System 358

11.7.3 LLR for MIMO System with a Candidate Vector Set 361

11.7.4 LLR for MIMO System Using a Limited Candidate Vector Set 364

Appendix 11.A Derivation of Equation (11.23) 370

12 Exploiting Channel State Information at the Transmitter Side 373

12.1 Channel Estimation on the Transmitter Side 373

12.1.1 Using Channel Reciprocity 374

12.1.2 CSI Feedback 374

12.2 Precoded OSTBC 375

12.3 Precoded Spatial-Multiplexing System 381

12.4 Antenna Selection Techniques 383

12.4.1 Optimum Antenna Selection Technique 384

12.4.2 Complexity-Reduced Antenna Selection 386

12.4.3 Antenna Selection for OSTBC 390

13 Multi-User MIMO 395

13.1 Mathematical Model for Multi-User MIMO System 396

13.2 Channel Capacity of Multi-User MIMO System 397

13.2.1 Capacity of MAC 398

13.2.2 Capacity of BC 399

13.3 Transmission Methods for Broadcast Channel 401

13.3.1 Channel Inversion 401

13.3.2 Block Diagonalization 404

13.3.3 Dirty Paper Coding (DPC) 408

13.3.4 Tomlinson-Harashima Precoding 412

References 419

Index 431

Über Autor(innen)

Yong Soo Cho is a Professor of Electronic Engineering at Chung-Ang University in Seoul, Korea. He has taught OFDM for 10 years and MIMO for 5. His research interests are in the areas of digital communication, digital signal processing, and FPGA Implementation. Cho has held positions at LG Electronics, the ETRI Mobile Communication Group, the WiBro Project Group, and was Chairman of the Wireless Access Working Group in Korea. He holds a BS from Chung-Ang University, an MS from Yonsei University, and a PhD from the University of Texas at Austin, all in electronic engineering.

Jaekwon Kim is an Assistant Professor of Computer and Telecommunications Engineering at Yonsei University. Prior to that he worked at Samsung Advanced Institute of Technology with the 4G System Team. He holds a BS and MS from Chung-Ang University and a PhD from the University of Texas at Austin, all in electronic engineering.

Won Y. Yang is a Professor of Electronic Engineering at Chung-Ang University. He has written two books on MATLAB in English, and two in Korean. Yang holds a BS and MS in Electrical Engineering from Seoul National University, an MS in Applied Math and a PhD in Electrical Engineering from the University of Southern California.

Chung Gu Kang is a Professor of Radio Communication and Engineering at Korea University. Previous work experience inlcudes time in the US spent at the Aerospace Corporation and Rockwell International, where he worked on telecommunications systems development. He was also a Visiting Associate Professor at the UC San Diego. His research interests are focesed on the cross layer design issues for MIMO/multiple access schemes for mobile broadband wireless access systems and MAC/routing protocols for mobile ad hoc networks. Kang holds a BS from UC San Diego and an MS and PhD in Electrical Engineering and Computer Engineering from UC Irvine.