Uniquely, this book proposes robust space-time code designs for real-world wireless channels. Through a unified framework, it emphasizes how propagation mechanisms such as space-time frequency correlations and coherent components impact the MIMO system performance under realistic power constraints. Combining a solid mathematical analysis with a physical and intuitive approach to space-time coding, the book progressively derives innovative designs, taking into consideration that MIMO channels are often far from ideal.
The various chapters of this book provide an essential, complete and refreshing insight into the performance behaviour of space-time codes in realistic scenarios and constitute an ideal source of the latest developments in MIMO propagation and space-time coding for researchers, R&D engineers and graduate students.
Features include Physical models and analytical representations of MIMO propagation channels, highlighting the strengths and weaknesses of various models Overview of space-time coding techniques, covering both classical and more recent schemes under information theory and error probability perspectives In-depth presentation of how real-world propagation affects the capacity and the error performance of MIMO transmission schemes Innovative and practical designs of robust space-time coding, precoding and antenna selection techniques for realistic propagation (including single-carrier and MIMO-OFDM transmissions)
"This book offers important insights into how space-time coding can be tailored for real-world MIMO channels. The discussion of MIMO propagation models is also intuitive and well-developed." Arogyaswami J. Paulraj, Professor, Stanford University, CA
"Finally a book devoted to MIMO from a new perspective that bridges the boundaries between propagat
- Presents space-time coding techniques for real-world MIMO channels
- Contains new design methodologies and criteria that guarantee the robustness of space-time coding in real life wireless communications applications
- Evaluates the performance of space-time coding in real world conditions
R&D communications engineers working in mobile and wireless communications, academic researchers, post graduate students.
Introduction to multi-antenna communications 1.1 Brief history of array processing 1.2 Space-time wireless channels for multi-antenna systems 1.3 Exploiting multiple antennas in wireless systems 1.4 Single-Input Multiple-Output systems 1.5 Multiple-Input Single-Output systems 1.6 Multiple-Input Multiple-Output systems 1.7 Multiple antenna techniques in commercial wireless systems
Physical MIMO channel modelling 2.1 Multidimensional channel modelling 2.2 Electromagnetic models 2.3 Geometry based models 2.4 Empirical models 2.5 Standardized models 2.6 Antennas in MIMO systems
Analytical MIMO channel representations for system design 3.1 General representations of correlated MIMO channels 3.2 Simplified representations of Gaussian MIMO channels 3.3 Propagation-motivated MIMO metrics 3.4 Relationship between physical models and analytical representations
Mutual information and capacity of real-world random MIMO channels 4.1 Capacity of fading channels with perfect transmit channel knowledge 4.2 Ergodic capacity of I.I.D. Rayleigh fast fading channels with partial transmit channel knowledge 4.3 Mutual information and capacity of correlated Rayleigh channels with partial transmit channel knowledge 4.4 Mutual information and capacity of Ricean channels with partial transmit channel knowledge 4.5 Mutual information in some particular channels 4.6 Outage capacity and diversity-multiplexing trade off in I.I.D. Rayleigh slow fading channels 4.7 Outage capacity and diversity-multiplexing trade-off in semi-correlated Raylaigh and Ricean slow fading channels
Space-time coding over I.I.D. Rayleigh flat fading channels 5.1 Overview of a space-time encoder 5.2 System model 5.3 Error probability motivated design methodology 5.4 Information theory motivated design methodology 5.5 Space-time block coding 5.6 Space-time trellis coding
Error probability in real-world MIMO channels 6.1 A conditional pairwise error probability approach 6.2 Introduction to an average pairwise error probability approach 6.3 Average pairwise error probability in Rayleigh fading channels 6.4 Average pairwise error probability in Ricean fading channels 6.5 Average pairwise error probability in dual-polarized channels 6.6 Perspectives on the space-time code design in realistic channels
Space-time coding over real-world MIMO channels with no transmit channel knowledge 7.1 Information theory motivated design methodology 7.2 Information theory motivated code design in slow fading channels 7.3 Error probability motivated design methodology 7.4 Error probability motivated code design in slow fading channels 7.5 Error probability motivated code design in fast fading channels
Space-time coding with partial transmit channel knowledge 8.1 Introduction to channel statistics based precoding techniques 8.2 Channel statistics based precoding for orthogonal space-time block coding 8.3 Channel statistics based precoding for codes with non identity error matrices 8.4 Channel statistics based precoding for spatial multiplexing 8.5 Introduction to quantized precoding and antenna selection techniques 8.6 Quantized precoding and antenna selection 8.7 Quantized precoding and antenna selection for orthogonal space-time block coding 8.8 Quantized precoding and antenna selection for spatial multiplexing 8.9 Information theory motivated quantized precoding
Space-time coding for frequency selective channels 9.1 Single-carrier vs multi-carrier transmissions 9.2 Information theoretic aspects for frequency selective MIMO channels 9.3 Average pairwise error probability 9.4 Code design criteria for single carrier transmissions in Rayleigh fading channels 9.5 Code design criteria for space-frequency coded MIMO-OFDM transmissions in Rayleigh fading channels 9.6 On the robustness of codes in spatially correlated frequency selective channels
Appendix A: Useful mathematical and matrix properties Appendix B: Complex Gaussian random variables and matrices Appendix C: SUI channel model Appendix D: Antenna coupling model Appendix E: Derivation of the average pairwise error probability
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- © Academic Press 2007
- 30th March 2007
- Academic Press
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Claude Oestges is Associate Professor with the Institute for Information and Communication Technologies, Electronics and Applied Mathematics (Université catholique de Louvain). His research interests cover wireless and satellite communications, with a specific focus on channel characterization and modeling. He is the author or co-author of two books and more than 170 scientific papers in international journals and conference proceedings.
Université catholique de Louvain, Belgium
Bruno Clerckx is Assistant Professor (Lecturer) at Imperial College London. He held research or visiting positions at Université catholique de Louvain, Stanford University, EURECOM and Samsung Electronics. His research interests cover wireless communications. He is the author of books, numerous scientific papers, standard contributions (3GPPLTE/LTE-A and IEEE802.16m) and patents.
Imperial College, London, UK
“This book offers important insights into how space-time coding can be tailored for real-world MIMO channels. The discussion of MIMO propagation models is also intuitive and well developed.” Professor Arogyaswami J. Paulraj, Stanford University, CA “Finally a book devoted to MIMO from a new perspective that bridges the boundaries between propagation, channel modeling, signal processing and space-time coding. It is of high reference value, combining intuitive and conceptual explanations with detailed, stringent derivations of basic facts of MIMO.” Ernst Bonek, Emeritus Professor, Technische Universität Wien, Austria