Space-Time Coding for Broadband Wireless Communications

ISBN-13: 9780471214793 / Angielski / Twarda / 2006 / 488 str.

Georgios B. Giannakis; Zhiqiang Liu; Xiaoli Ma

Opis

This is the first book on space-time coding for wireless communications, one of the most promising techniques for ensuring bandwidth efficiency. The text describes theoretical principles as well as engineering applications; discusses key criteria in the design of practical space-time codes; and covers single-carrier and multi-carrier transmission for both single- and multi-user communications.

Spis treści

Preface. Acronyms. 1. Motivation and Context. 1.1 Evolution of Wireless Communication Systems. 1.2 Wireless Propagation Effects. 1.3 Parameters and Classification of Wireless Channels. 1.3.1 Delay Spread and Coherence Bandwidth. 1.3.2 Doppler Spread and Coherence Time. 1.4 Providing, Enabling and Collecting Diversity. 1.4.1 Diversity Provided by Frequency–Selective Channels. 1.4.2 Diversity Provided by Time–Selective Channels. 1.4.3 Diversity Provided by Multi–Antenna Channels. 1.5 Chapter–by–Chapter Organization. 2. Fundamentals of ST Wireless Communications. 2.1 Generic ST System Model. 2.2 ST Coding viz Channel Coding. 2.3 Capacity of ST Channels. 2.3.1 Outage Capacity. 2.3.2 Ergodic Capacity. 2.4 Error Performance of ST Coding. 2.5 Design Criteria for ST Codes. 2.6 Diversity and Rate: Finite SNR viz Asymptotics. 2.7 Classification of ST Codes. 2.8 Closing Comments. 3. Coherent ST Codes for Flat Fading Channels. 3.1 Delay Diversity ST Codes. 3.2 ST Trellis Codes. 3.2.1 Trellis Representation. 3.2.2 TSC ST Trellis Codes. 3.2.3 BBH ST Trellis Codes. 3.2.4 GFK ST Trellis Codes. 3.2.5 Viterbi Decoding of ST Trellis Codes. 3.3 Orthogonal ST Block Codes. 3.3.1 Encoding of OSTBCs. 3.3.2 Linear ML Decoding of OSTBCs. 3.3.3 BER Performance with OSTBCs. 3.3.4 Channel Capacity with OSTBCs. 3.4 Quasi–Orthogonal ST Block Codes. 3.5 ST Linear Complex Field Codes. 3.5.1 Antenna Switching and Linear Precoding. 3.5.2 Designing Linear Precoding Matrices. 3.5.3 Upper–Bound on Coding Gain. 3.5.4 Construction based on Parameterization. 3.5.5 Construction Based on Algebraic Tools. 3.5.6 Decoding ST Linear Complex Field Codes. 3.5.7 Modulus–Preserving STLCFC. 3.6 Linking OSTBC, QO–STBC and STLCFC Designs. 3.6.1 Embedding MP–STLCFC into the Alamouti Code. 3.6.2 Embedding 2 x 2 MP–STLCFCs into OSTBC. 3.6.3 Decoding QO–MP–STLCFC. 3.7 Closing Comments. 4. Layered ST Codes. 4.1 BLAST Designs. 4.1.1 D–BLAST. 4.1.2 V–BLAST. 4.1.3 Rate Performance with BLAST Codes. 4.2 ST Codes Trading Diversity for Rate. 4.2.1 Layered ST Codes with Antenna–Grouping. 4.2.2 Layered High–Rate Codes. 4.3 Full–Diversity Full–Rate ST Codes. 4.3.1 The FDFR Transceiver. 4.3.2 Algebraic FDFR Code Design. 4.3.3 Mutual Information Analysis. 4.3.4 Diversity–Rate–Performance Trade–offs. 4.4 Numerical Examples. 4.5 Closing Comments. 5. Sphere Decoding and (Near–) Optimal MIMO Demodulation. 5.1 Sphere Decoding Algorithm. 5.1.1 Selecting a Finite Search Radius. 5.1.2 Initializing with Unconstrained LS. 5.1.3 Searching within the Fixed–Radius Sphere. 5.2 Average Complexity of SDA in Practice. 5.3 SDA Improvements. 5.3.1 SDA with Detection Ordering and Nulling–Cancelling. 5.3.2 Schnorr–Euchner Variate of SDA. 5.3.3 SDA with Increasing Radius Search. 5.3.4 Simulated Comparisons. 5.4 Reduced–Complexity IRS–SDA. 5.5 Soft Decision Sphere Decoding. 5.5.1 List Sphere Decoding (LSD). 5.5.2 Soft SDA using Hard SDAs. 5.6 Closing Comments. 6. Non–Coherent and Differential ST Codes for Flat Fading Channels. 6.1 Non–Coherent ST Codes. 6.1.1 Search–Based Designs. 6.1.2 Training–Based Designs. 6.2 Differential ST Codes. 6.2.1 Scalar Differential Codes. 6.2.2 Differential Unitary ST Codes. 6.2.3 Differential Alamouti Codes. 6.2.4 Differential OSTBCs. 6.2.5 Cayley Differential Unitary ST Codes. 6.3 Closing Comments. 7. ST Codes for Frequency–Selective Fading Channels: Single–Carrier Systems. 7.1 System Model and Performance Limits. 7.1.1 Flat–Fading Equivalence and Diversity. 7.1.2 Rate Outage Probability. 7.2 ST Trellis Codes. 7.2.1 Generalized Delay Diversity. 7.2.2 Search–Based STTC Construction. 7.2.3 Numerical Examples. 7.3 ST Block Codes. 7.3.1 Block Coding with Two Transmit–Antennas. 7.3.2 Receiver Processing. 7.3.3 ML Decoding based on the Viterbi Algorithm. 7.3.4 Turbo Equalization. 7.3.5 Multi–Antenna Extensions. 7.3.6 OSTBC Properties. 7.3.7 Numerical Examples. 7.4 Closing Comments. 8. ST Codes for Frequency–Selective Fading Channels: Multi–Carrier Systems. 8.1 The General MIMO OFDM Framework. 8.1.1 OFDM Basics. 8.1.2 MIMO OFDM. 8.1.3 STF Framework. 8.2 ST and SF Coded MIMO OFDM. 8.3 STF Coded OFDM. 8.3.1 Subcarrier Grouping. 8.3.2 GSTF Block Codes. 8.3.3 GSTF Trellis Codes. 8.3.4 Numerical Examples. 8.4 Digital Phase Sweeping and Block Circular Delay. 8.5 Full–Diversity Full–Rate MIMO OFDM. 8.5.1 Encoders and Decoders. 8.5.2 Diversity and Rate Analysis. 8.5.3 Numerical Examples. 8.6 Closing Comments. 9. ST Codes for Time–Varying Channels. 9.1 Time–Varying Channels. 9.1.1 Channel Models. 9.1.2 Time–Frequency Duality. 9.1.3 Doppler Diversity. 9.2 Space–Time–Doppler Block Codes. 9.2.1 Duality–Based STDO Codes. 9.2.2 Phase Sweeping Design. 9.3 Space–Time–Doppler FDFR Codes. 9.4 Space–Time–Doppler Trellis Codes. 9.4.1 Design Criterion. 9.4.2 Smart–Greedy Codes. 9.5 Numerical Examples. 9.6 Space–Time–Doppler Differential Codes. 9.6.1 Inner Codec. 9.6.2 Outer Differential Codec. 9.7 ST Codes for Doubly–Selective Channels. 9.7.1 Numerical Examples. 9.8 Closing Comments. 10. Joint Galois–Field and Linear Complex–Field ST Codes. 10.1 GF–LCF ST Codes. 10.1.1 Separate versus Joint GF–LCF ST Coding. 10.1.2 Performance Analysis. 10.1.3 Turbo Decoding. 10.2 GF–LCF ST Layered Codes. 10.2.1 GF–LCF ST FDFR Codes: QPSK Signalling. 10.2.2 GF–LCF ST FDFR Codes: QAM Signalling. 10.2.3 Performance Analysis. 10.2.4 GF–LCF FDFR versus GF–Coded V–BLAST. 10.2.5 Numerical Examples. 10.3 GF–LCF Coded MIMO OFDM. 10.3.1 Joint GF–LCF Coding and Decoding. 10.3.2 Numerical Examples. 10.4 Closing Comments. 11. MIMO Channel Estimation and Synchronization. 11.1 Preamble–Based Channel Estimation. 11.2 Optimal Training–Based Channel Estimation. 11.2.1 ZP–Based Block Transmissions. 11.2.2 CP–Based Block Transmissions. 11.2.3 Special Cases. 11.2.4 Numerical Examples. 11.3 (Semi–)Blind Channel Estimation. 11.4 Joint Symbol Detection and Channel Estimation. 11.4.1 Decision–Directed Methods. 11.4.2 Kalman Filtering Based Methods. 11.5 Carrier Synchronization. 11.5.1 Hopping Pilot Based CFO Estimation. 11.5.2 Blind CFO Estimation. 11.5.3 Numerical Examples. 11.6 Closing Comments. 12. ST Codes with Partial Channel Knowledge: Statistical CSI. 12.1 Partial CSI Models. 12.1.1 Statistical CSI. 12.2 ST Spreading. 12.2.1 Average Error Performance. 12.2.2 Optimization based on Average SER Bound. 12.2.3 Mean–Feedback. 12.2.4 Covariance–Feedback. 12.2.5 Beamforming Interpretation. 12.3 Combining OSTBC with Beamforming. 12.3.1 Two–Dimensional Coder–Beamformer. 12.4 Numerical Examples. 12.4.1 Performance with Mean–Feedback. 12.4.2 Performance with Covariance–Feedback. 12.5 Adaptive Modulation for Rate Improvement. 12.5.1 Numerical Examples. 12.6 Optimizing Average Capacity. 12.7 Closing Comments. 13. ST Codes With Partial Channel Knowledge: Finite–Rate CSI. 13.1 General Problem Formulation. 13.2 Finite–Rate Beamforming. 13.2.1 Beamformer Selection. 13.2.2 Beamformer Codebook Design. 13.2.3 Quantifying the Power Loss. 13.2.4 Numerical Examples. 13.3 Finite–Rate Precoded Spatial Multiplexing. 13.3.1 Precoder Selection Criteria. 13.3.2 Codebook Construction: Infinite–Rate. 13.3.3 Codebook Construction: Finite–Rate. 13.3.4 Numerical Examples. 13.4 Finite–Rate Precoded OSTBC. 13.4.1 Precoder Selection Criterion. 13.4.2 Codebook Construction: Infinite–Rate. 13.4.3 Codebook Construction: Finite–Rate. 13.4.4 Numerical Examples. 13.5 Capacity Optimization with Finite–Rate Feedback. 13.5.1 Selection Criterion. 13.5.2 Codebook Design. 13.6 Combining Adaptive Modulation with Beamforming. 13.6.1 Mode Selection. 13.6.2 Codebook Design. 13.7 Finite–rate Feedback in MIMO OFDM. 13.8 Closing Comments. 14. ST Codes in the Presence of Interference. 14.1 ST Spreading. 14.1.1 Maximizing the Average SINR. 14.1.2 Minimizing the Average Error Bound. 14.2 Combining STS with OSTBC. 14.2.1 Low–Complexity Receivers. 14.3 Optimal Training with Interference. 14.3.1 LS Channel Estimation. 14.3.2 LMMSE Channel Estimation. 14.4 Numerical Examples. 14.5 Closing Comments. 15. ST Codes for Orthogonal Multiple Access. 15.1 System Model. 15.1.1 Synchronous downlink. 15.1.2 Quasi–synchronous uplink. 15.2 Single–Carrier Systems: STBC–CIBS–CDMA. 15.2.1 CIBS–CDMA for User Separation. 15.2.2 STBC Encoding and Decoding. 15.2.3 Attractive Features of STBC–CIBS–CDMA. 15.2.4 Numerical Examples. 15.3 Multi–Carrier Systems: STF–OFDMA. 15.3.1 OFDMA for User Separation. 15.3.2 STF Block Codes. 15.3.3 Attractive Features of STF–OFDMA. 15.3.4 Numerical Examples. 15.4 Closing Comments. References. Index.

O autorze

GEORGIOS B. GIANNAKIS, PhD, is ADC Endowed Chair Professor in Wireless Telecommunications with the Department of Electrical and Computer Engineering at the University of Minnesota. He is a Fellow of the IEEE, a (co–)recipient of six IEEE best paper awards (including the IEEE Communication Society′s 2004 Guglielmo Marconi Prize Paper), and a recipient of the IEEE Signal Processing Society′s Technical Achievement Award. His interests and expertise span the areas of wireless communications, wireless networks, sensor networks, and statistical signal processing.

ZHIQIANG LIU, PhD, is Assistant Professor with the Department of Electrical and Computer Engineering at the University of Iowa. His research interests include space–time coding and processing, wireless communications theory, synchronization, channel estimation, and sensor networks.

XIAOLI MA, PhD, is Assistant Professor with the School of Electrical and Computer Engineering at the Georgia Institute of Technology. Her research interests include signal processing for communications and networking, signal estimation algorithms, wireless communications theory, and sensor networks.

SHENGLI ZHOU, PhD, is Assistant Professor with the Department of Electrical and Computer Engineering at the University of Connecticut. His research interests include wireless communications and signal processing, underwater acoustic communications and networking, and wireless positioning and synchronization.

Blurb

The state of the art in space–time code design

This cutting–edge text presents the state of the art in space–time (ST) coded multi–antenna systems operating over broadband wireless mobile channels, including an analysis of the most recent research findings. Specifically, the authors focus on the algorithms and performance analysis of ST coded systems at the physical layer.

This text is a complement to previously published works covering ST coded multi–antenna systems and offers several unique features and benefits:

• Systematic coverage of one of the most promising techniques that will support the next generation of broadband multimedia services
• Unified and comprehensive exposition on the design of ST codes, which places all the latest research in context
• Thorough designs of ST codes for the gamut of frequency–selective, time–selective, and doubly–selective MIMO channels that are encountered with broadband wireless mobile links, in addition to ST codes for flat fading MIMO channels
• Recent advances in complex field coded transmissions, sphere decoding algorithms, closed–loop ST coded systems, operation in the presence of colored interference, and multi–user, multi–antenna systems
• Development and analysis of novel algorithms and techniques that have arisen from recent research

Numerical and simulated examples are given for most of the algorithms presented in the text to help readers better visualize and understand how they work. In addition, the authors provide background information on wireless communications basics, diversity techniques, and capacity of MIMO channels, giving readers the necessary foundation to grasp all the key concepts and techniques presentedin the text.

This text will not only bring engineers, network designers, and graduate students in wireless communications up to date with the latest findings, it will also provide them with the latest applications.