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Large MIMO Systems

Book Description

Large MIMO systems, with tens to hundreds of antennas, are a promising emerging communication technology. This book provides a unique overview of this technology, covering the opportunities, engineering challenges, solutions, and state-of-the-art of large MIMO test beds. There is in-depth coverage of algorithms for large MIMO signal processing, based on meta-heuristics, belief propagation and Monte Carlo sampling techniques, and suited for large MIMO signal detection, precoding, and LDPC code designs. The book also covers the training requirement and channel estimation approaches in large-scale point-to-point and multi-user MIMO systems; spatial modulation is also included. Issues like pilot contamination and base station cooperation in multi-cell operation are addressed. A detailed exposition of MIMO channel models, large MIMO channel sounding measurements in the past and present, and large MIMO test beds is also presented. An ideal resource for academic researchers, next generation wireless system designers and developers, and practitioners in wireless communications.

Table of Contents

  1. Cover
  2. Half Title
  3. Endorsements
  4. Title
  5. Copyright
  6. Dedication
  7. Contents
  8. Preface
  9. Acknowledgments
  10. Abbreviations
  11. Notation
  12. 1 Introduction
    1. 1.1 Multiantenna wireless channels
    2. 1.2 MIMO system model
    3. 1.3 MIMO communication with CSIR-only
      1. 1.3.1 Slow fading channels
      2. 1.3.2 Fast fading channels
    4. 1.4 MIMO communication with CSIT and CSIR
    5. 1.5 Increasing spectral efficiency: quadrature amplitude modulation (QAM) vs MIMO
    6. 1.6 Multiuser MIMO communication
    7. 1.7 Organization of the book
    8. References
  13. 2 Large MIMO systems
    1. 2.1 Opportunities in large MIMO systems
    2. 2.2 Channel hardening in large dimensions
    3. 2.3 Technological challenges and solution approaches
      1. 2.3.1 Availability of independent spatial dimensions
      2. 2.3.2 Placement of a large number of antennas and RF chains
      3. 2.3.3 Low complexity large MIMO signal processing
      4. 2.3.4 Multicell operation
    4. References
  14. 3 MIMO encoding
    1. 3.1 Spatial multiplexing
    2. 3.2 Space-time coding
      1. 3.2.1 Space-time block codes
      2. 3.2.2 High-rate NO-STBCs
      3. 3.2.3 NO-STBCs from CDAs
    3. 3.3 Spatial modulation (SM)
      1. 3.3.1 SM
      2. 3.3.2 SSK
      3. 3.3.3 GSM
    4. References
  15. 4 MIMO detection
    1. 4.1 System model
    2. 4.2 Optimum detection
    3. 4.3 Linear detection
    4. 4.4 Interference cancelation
    5. 4.5 LR-aided linear detection
      1. 4.5.1 LR-aided detection
      2. 4.5.2 SA
    6. 4.6 Sphere decoding
    7. References
  16. 5 Detection based on local search
    1. 5.1 LAS
      1. 5.1.1 System model
      2. 5.1.2 Multistage LAS algorithm
      3. 5.1.3 Complexity
      4. 5.1.4 Generation of soft outputs
      5. 5.1.5 Near-optimal performance in large dimensions
      6. 5.1.6 Decoding of large NO-STBCs using LAS
    2. 5.2 Randomized search (RS)
      1. 5.2.1 RS algorithm
      2. 5.2.2 Performance and complexity
    3. 5.3 Reactive tabu search (RTS)
      1. 5.3.1 RTS algorithm
      2. 5.3.2 RTS algorithm versus LAS algorithm
      3. 5.3.3 Performance and complexity of RTS
      4. 5.3.4 LTS
      5. 5.3.5 R3TS
      6. 5.3.6 Lower bounds on ML performance using RTS
    4. References
  17. 6 Detection based on probabilistic data association (PDA)
    1. 6.1 PDA in communication problems
    2. 6.2 PDA based MIMO detection
      1. 6.2.1 Real-valued bit-wise system model
      2. 6.2.2 Iterative procedure
      3. 6.2.3 Complexity reduction
    3. 6.3 Performance results
      1. 6.3.1 Performance in large V-BLAST MIMO
      2. 6.3.2 PDA versus LAS performance in NO-STBC MIMO
    4. References
  18. 7 Detection/decoding based on message passing on graphical models
    1. 7.1 Graphical models
      1. 7.1.1 Bayesian belief networks
      2. 7.1.2 Markov random fields
      3. 7.1.3 Factor graphs
    2. 7.2 BP
      1. 7.2.1 BP in communication problems
      2. 7.2.2 BP algorithm on factor graphs
      3. 7.2.3 BP algorithm on pair-wise MRFs
      4. 7.2.4 Loopy BP
      5. 7.2.5 Damped BP
    3. 7.3 Application of BP in MIMO – an example
      1. 7.3.1 MIMO-ISI system model
      2. 7.3.2 Detection using BP
      3. 7.3.3 Performance and complexity
    4. 7.4 Large MIMO detection using MRF
      1. 7.4.1 MRF BP based detection algorithm
      2. 7.4.2 MRF potentials
      3. 7.4.3 Message passing
      4. 7.4.4 Performance
      5. 7.4.5 Complexity
    5. 7.5 Large MIMO detection using a factor graph
      1. 7.5.1 Computation complexity
      2. 7.5.2 Performance
      3. 7.5.3 Vector GA (VGA) in PDA versus SGA in FG BP
    6. 7.6 BP with the Gaussian tree approximation (GTA)
    7. 7.7 BP based joint detection and LDPC decoding
      1. 7.7.1 System model
      2. 7.7.2 Individual detection and decoding
      3. 7.7.3 Joint detection and decoding
      4. 7.7.4 Performance and complexity
    8. 7.8 Irregular LDPC codes design for large MIMO
      1. 7.8.1 EXIT chart analysis
      2. 7.8.2 LDPC code design
      3. 7.8.3 Coded BER performance
    9. References
  19. 8 Detection based on MCMC techniques
    1. 8.1 Monte Carlo integration
    2. 8.2 Markov chains
    3. 8.3 MCMC techniques
      1. 8.3.1 Metropolis–Hastings algorithm
      2. 8.3.2 Simulated annealing
      3. 8.3.3 Gibbs sampling
    4. 8.4 MCMC based large MIMO detection
      1. 8.4.1 System model
      2. 8.4.2 Conventional Gibbs sampling for detection
      3. 8.4.3 Motivation for mixed-Gibbs sampling (MGS)
      4. 8.4.4 MGS
      5. 8.4.5 Effect of mixing ratio q
      6. 8.4.6 Stopping criterion
      7. 8.4.7 Performance and complexity of the MGS algorithm
      8. 8.4.8 Multirestart MGS algorithm for higher-order QAM
      9. 8.4.9 Effect of multiple restarts
      10. 8.4.10 MGS with multiple restarts
      11. 8.4.11 Restart criterion
      12. 8.4.12 Performance and complexity of the MGS-MR algorithm
      13. 8.4.13 Performance of the MGS-MR as a function of loading factor
    5. References
  20. 9 Channel estimation in large MIMO systems
    1. 9.1 MIMO capacity with imperfect CSI
    2. 9.2 How much training is required?
      1. 9.2.1 Point-to-point MIMO training
      2. 9.2.2 Multiuser MIMO training
    3. 9.3 Large multiuser MIMO systems
      1. 9.3.1 System model
      2. 9.3.2 Iterative channel estimation/detection in frequency-flat fading
      3. 9.3.3 Iterative channel estimation/equalization in ISI channels
      4. 9.3.4 Equalization using initial channel estimates
      5. 9.3.5 Equalization using the MGS-MR algorithm
    4. References
  21. 10 Precoding in large MIMO systems
    1. 10.1 Precoding in point-to-point MIMO
      1. 10.1.1 SVD precoding
      2. 10.1.2 Pairing of good and bad subchannels
      3. 10.1.3 Performance of X-codes and Y-codes
    2. 10.2 Precoding in a multiuser MIMO downlink
      1. 10.2.1 Linear precoding
      2. 10.2.2 Non-linear precoding
      3. 10.2.3 Precoding in large multiuser MISO systems
      4. 10.2.4 Precoder based on norm descent search (NDS)
      5. 10.2.5 Complexity and performance
      6. 10.2.6 Closeness to sum capacity
    3. 10.3 Multicell precoding
      1. 10.3.1 System model
      2. 10.3.2 Precoding without BS cooperatio
      3. 10.3.3 Precoding with BS cooperation
      4. 10.3.4 Performance
    4. References
  22. 11 MIMO channel models
    1. 11.1 Analytical channel models
      1. 11.1.1 Spatial correlation based models
      2. 11.1.2 Propagation based models
    2. 11.2 Effect of spatial correlation on large MIMO performance: an illustration
      1. 11.2.1 Pinhole effect
      2. 11.2.2 Effect of spatial correlation on LAS detector performance
    3. 11.3 Standardized channel models
      1. 11.3.1 Models in IEEE 802.11 WiFi
      2. 11.3.2 Models in 3GPP/LTE
    4. 11.4 Large MIMO channel measurement campaigns
    5. 11.5 Compact antenna arrays
      1. 11.5.1 PIFA
      2. 11.5.2 PIFAs as elements in compact arrays
      3. 11.5.3 MIMO cubes
    6. References
  23. 12 Large MIMO testbeds
    1. 12.1 12 × 12 point-to-point MIMO system
    2. 12.2 8 × 16 point-to-point MIMO system at 10 Gbps rate
    3. 12.3 16 × 16 multiuser MIMO system
    4. 12.4 64 × 15 multiuser MIMO system (Argos)
    5. 12.5 32 × 14 multiuser MIMO system (Ngara)
    6. 12.6 Summary
    7. References
  24. Author index
  25. Subject index