MIMO detection using Markov chain Monte Carlo techniques for near-capacity performance

  title={MIMO detection using Markov chain Monte Carlo techniques for near-capacity performance},
  author={Haidong Zhu and Zhenning Shi and Behrouz Farhang-Boroujeny},
  journal={Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005.},
  pages={iii/1017-iii/1020 Vol. 3}
In this paper, we develop a new soft-in soft-out (SISO) multiple-input multiple-output (MIMO) detection algorithm using the Markov chain Monte Carlo (MCMC) simulation techniques and study its performance when applied to a MIMO communication system. Comparison with the best MIMO detection algorithm in the current literature, sphere decoding, shows that the proposed detection algorithm can improve the gap between the present results and the capacity by as much as 2 dB. 
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A comparison of optimal and sub-optimal MAP decoding algorithms operating in the log domain,

  • P. Robertson, E. Villebrun, P Hoeher
  • Monte Carlo Statistical Methods
  • 1995
Highly Influential
4 Excerpts

A new approach to layered space-time coding and signal processing,

  • H. E. Gamal, A. R. Hammons, Jr.
  • IEEE Trans Info. Theory,
  • 2001
2 Excerpts

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