- A comprehensive book on coding for MIMO techniques covering main strategies
- Theories and practical issues on MIMO communications are examined in detail
- Easy to follow and accessible for both beginners and experienced practitioners in the field
- References at the end of each chapter for further reading
- Can be used with ease as a research book, or a textbook on a graduate or advanced undergraduate level course
This book is aimed at advanced undergraduate and postgraduate students, researchers and practitioners in industry, as well as individuals working for government, military, science and technology institutions who would like to learn more about coding for MIMO communication systems.
List of Figures.
List of Tables.
1.1 Need for MIMO Systems.
1.2 MIMO Communications in Wireless Standards .
1.3 Organization of the Book.
1.4 Other Topics in MIMO Systems.
2 Fading Channels and Diversity Techniques.
2.1 Wireless Channels.
2.1.1 Path Loss, Shadowing and Small Scale Fading.
2.1.2 Fading Channel Models.
2.2 Error/Outage Probabilities over Fading Channels.
2.2.1 Outage Probability for Rayleigh Fading Channels.
2.2.2 Average Error Probabilities over Rayleigh Fading Channels.
2.2.3 Extensions to Other Fading Channels.
2.2.4 Performance over Frequency Selective Fading Channels.
2.3 Diversity Techniques.
2.3.1 Types of Diversity.
2.3.2 System Model for Lth Order Diversity.
2.3.3 Maximal Ratio Combining (MRC).
2.3.4 Suboptimal Combining Algorithms.
2.3.5 Selection Combining.
2.4 Channel Coding as a Means of Time Diversity.
2.4.1 Block Coding over a Fully Interleaved Channel.
2.4.2 Convolutional Coding.
2.5 Multiple Antennas in Wireless Communications.
2.5.1 Receive Diversity.
2.5.2 Smart Antennas and Beamforming.
2.6 Chapter Summary and Further Reading .
3 Capacity and Information Rates of MIMO Channels.
3.1 Capacity and Information Rates of Noisy Channels.
3.2 Capacity and Information Rates of AWGN and Fading Channels.
3.2.1 AWGN Channels.
3.2.2 Fading Channels.
3.3 Capacity of MIMO Channels.
3.3.1 Deterministic MIMO Channels.
3.3.2 Ergodic MIMO Channels.
3.3.3 Non–Ergodic MIMO Channels and Outage Capacity.
3.3.4 Transmit CSI for MIMO Fading Channels.
3.4 Constrained Signaling for MIMO Communications.
3.5 Discussion: Why Use MIMO Systems?
3.6 Chapter Summary and Further Reading.
4 Space–Time Block Codes.
4.1 Transmit Diversity with Two Antennas: The Alamouti Scheme.
4.1.1 Transmission Scheme.
4.1.2 Optimal Receiver for the Alamouti Scheme.
4.1.3 Performance Analysis of the Alamouti Scheme.
4.2 Orthogonal Space–Time Block Codes.
4.2.1 Linear Orthogonal Designs.
4.2.2 Decoding of General Space–Time Block Codes.
4.2.3 Performance Analysis of Space–Time Block Codes.
4.3 Quasi–Orthogonal Space–Time Block Codes.
4.4 Linear Dispersion Codes.
4.5 Chapter Summary and Further Reading.
5 Space–Time Trellis Codes.
5.1 A Simple Space–Time Trellis Code.
5.2 General Space–Time Trellis Codes.
5.2.1 Notation and Preliminaries.
5.2.2 Decoding of Space–Time Trellis Codes.
5.3 Basic Space–Time Code Design Principles.
5.3.1 Pairwise Error Probability.
5.3.2 Space–Time Code Design Principles.
5.3.3 Examples of Good Space–Time Codes.
5.3.4 Space–Time Trellis Codes for Fast Fading Channels.
5.4 Representation for Space–Time Trellis Codes for PSK Constellations.
5.4.1 Generator Matrix Representation.
5.4.2 Improved Space–Time Code Design.
5.5 Performance Analysis for Space–Time Trellis Codes.
5.5.1 Union Bound for Space–Time Trellis Codes.
5.5.2 Useful Performance Bounds for Space–Time Trellis Codes.
5.6 Comparison of Space–Time Block and Trellis Codes.
5.7 Chapter Summary and Further Reading.
6 Layered Space–Time Codes.
6.1 Basic Bell Labs Layered Space–Time (BLAST) Architectures.
6.1.2 Detection Algorithms for Basic BLAST Architectures.
6.2 Diagonal BLAST (DBLAST).
6.2.1 Detection Algorithms for DBLAST.
6.3 Multilayered Space–Time Coding.
6.3.1 Encoder Structure.
6.3.2 Group Interference Cancellation Detection.
6.4 Threaded Space–Time Codes.
6.4.1 Layering Approach.
6.4.2 Threaded Space–Time Code Design.
6.4.4 Detection of Threaded Space–Time Codes.
6.5 Other Detection Algorithms for Spatial Multiplexing Systems.
6.5.1 Greedy Detection.
6.5.2 Belief Propagation Detection.
6.5.3 Turbo–BLAST Detection.
6.5.4 Reduced Complexity ZF/MMSE Detection.
6.5.5 Sphere Decoding.
6.6 Diversity/Multiplexing Gain Trade–off .
6.7 Chapter Summary and Further Reading.
7 Concatenated Codes and Iterative Decoding.
7.1 Development of Concatenated Codes.
7.2 Concatenated Codes for AWGN Channels.
7.2.1 Encoder Structures.
7.2.2 Iterative Decoder Structures.
7.2.3 The SOVA Decoder.
7.2.4 Performance with Maximum Likelihood Decoding.
7.3 Concatenated Codes for MIMO Channels.
7.3.1 Concatenated Space–Time Turbo Coding Scheme.
7.3.2 Turbo Space–Time Trellis Coding Scheme.
7.3.3 Turbo Space–Time Coding Scheme.
7.4 Turbo Coded Modulation for MIMO Channels.
7.4.1 Encoder Structure.
7.4.2 Decoder Structure.
7.5 Concatenated Space–Time Block Coding.
7.5.1 Encoder Structure.
7.5.2 Decoder Structure.
7.5.3 Performance Analysis.
7.6 Chapter Summary and Further Reading.
8 Unitary and Differential Space–Time Codes.
8.1 Capacity of Noncoherent MIMO Channels.
8.1.1 Channel Capacity.
8.1.2 Capacity Achieving Signals.
8.2 Unitary Space–Time Codes.
8.2.1 USTC Encoder.
8.2.2 ML Detection of USTCs.
8.2.3 Performance Analysis.
8.2.4 Construction of Unitary Space–Time Signals.
8.3 Differential Space–Time Codes.
8.3.1 Differential Space–Time Coding for Single Antenna Systems.
8.3.2 Differential Space–Time Coding for MIMO Systems.
8.4 Turbo Coded Unitary Space–Time Codes.
8.4.1 Encoder Structure.
8.4.2 Noncoherent Iterative Decoder.
8.5 Trellis Coded Unitary Space–Time Codes.
8.6 Turbo Coded Differential Space–Time Codes.
8.6.1 Encoder Structure.
8.6.2 Iterative Detectors.
8.7 Chapter Summary and Further Reading.
9 Space–Time Coding for Frequency Selective Fading Channels.
9.1 MIMO Frequency Selective Channels.
9.2 Capacity and Information Rates of MIMO Frequency Selective Fading Channels.
9.2.1 Information Rates with Gaussian Inputs.
9.2.2 Achievable Information Rates with Practical Constellations.
9.3 Space–Time Coding for MIMO FS Channels.
9.3.1 Interpretation of MIMO FS Channels Using Virtual Antennas.
9.3.2 A Simple Full Diversity Code for MIMO FS Channels.
9.3.3 Space–Time Trellis Codes for MIMO FS Channels.
9.3.4 Concatenated Coding for MIMO FS Channels.
9.3.5 Spatial Multiplexing for MIMO FS Channels.
9.4 Channel Detection for MIMO FS Channels.
9.4.1 Linear Equalization for MIMO FS Channels.
9.4.2 Decision Feedback Equalization for MIMO FS Channels.
9.4.3 Soft Input Soft Output Channel Detection.
9.4.4 Other Reduced Complexity Approaches.
9.5 MIMO OFDM Systems.
9.5.1 MIMO–OFDM Channel Model.
9.5.2 Space–Frequency Coding.
9.5.3 Challenges in MIMO–OFDM.
9.6 Chapter Summary and Further Reading.
10 Practical Issues in MIMO Communications.
10.1 Channel State Information Estimation.
10.1.1 CSI Estimation Using Pilot Tones.
10.1.2 What to Do with CSI?
10.1.3 Space–Time Coding Examples with Estimated CSI.
10.2 Spatial Channel Correlation for MIMO Systems.
10.2.1 Measurements and Modeling of Spatial Correlation.
10.2.2 Spatial Channel Correlation Models.
10.2.3 Channel Capacity with Spatial Correlation.
10.2.4 Space–Time Code Performance with Spatial Correlation.
10.3 Temporal Channel Correlation.
10.4 MIMO Communication System Design Issues.
10.5 Chapter Summary and Further Reading.
11 Antenna Selection for MIMO Systems.
11.1 Capacity–based Antenna Selection.
11.1.1 System Model.
11.1.2 Optimal Selection.
11.1.3 Simplified (Suboptimal) Selection.
11.2 Energy–based Antenna Selection.
11.3 Antenna Selection for Space–Time Trellis Codes.
11.3.1 Quasi–Static Fading Channels.
11.3.2 Block Fading Channels.
11.3.3 Fast Fading Channels.
11.4 Antenna Selection for Space–Time Block Codes.
11.4.1 Receive Antenna Selection.
11.4.2 Transmit Antenna Selection.
11.5 Antenna Selection for Combined Channel Coding and Orthogonal STBCs.
11.5.1 Performance Analysis.
11.6 Antenna Selection for Frequency Selective Channels.
11.7 Antenna Selection with Nonidealities.
11.7.1 Impact of Spatial Correlation.
11.7.3 Impact of Channel Estimation Error.
11.8 Chapter Summary and Further Reading.
Ali Ghrayeb received the Ph.D. degree in electrical engineering from the University of Arizona, Tucson, AZ, in May 2000. He is currently an Associate Professor in the Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada. He holds a Concordia Research Chair in High–Speed Wireless Communications. His research interests are in wireless and mobile communications, wireless networks, and coding and signal processing for data transmission and storage. He has co–instructed technical tutorials and short courses on coding for MIMO Systems and on Synchronization for WCDMA Systems at several major IEEE conferences. He serves as an Associate Editor for IEEE Transactions on Vehicular Technology and Wiley Wireless Communications and Mobile Computing Journal.