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.
A. Chockalingam is a professor in the Department of Electrical Communication Engineering, Indian Institute of Science (IISc), Bangalore, India. He has made pioneering contributions in the area of low-complexity near-optimal signal detection in large MIMO systems. He is a recipient of the Swarnajayanti Fellowship from the Department of Science and Technology, Government of India, and a Fellow of the Indian National Academy of Engineering (INAE), the National Academy of Sciences, India (NASI) and the Indian National Science Academy (INSA). B. Sundar Rajan is a professor in the Department of Electrical Communication Engineering, Indian Institute of Science (IISc), Bangalore, India. He is a well-known authority in the area of space-time coding for MIMO channels and distributed space-time coding, and a leading expert in the design of space-time codes based on algebraic techniques. He is a recipient of the Professor Rustum Choksi Award from IISc for excellence in research in engineering, and a Fellow of the Indian National Academy of Engineering (INAE), the National Academy of Sciences, India (NASI), the Indian National Science Academy (INSA) and the Indian Academy of Sciences (IASc).
1. Introduction; 2. Large MIMO systems; 3. MIMO encoding; 4. MIMO detection; 5. Detection based on local search; 6. Detection based on probabilistic data association; 7. Detection/decoding based on message passing on graphical models; 8. Detection based on MCMC techniques; 9. Channel estimation in large MIMO systems; 10. Precoding in large MIMO systems; 11. MIMO channel models; 12. Large MIMO test beds.