MIMO Detection Using Markov Chain Monte Carlo Techniques for Near-Capacity Performance

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Zhu, Haidong
Shi, Zhenning
Farhang-Boroujeny, Behrouz

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Institute of Electrical and Electronics Engineers (IEEE Inc)

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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, the sphere decoding, show 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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Proceedings of ICCASP 2005

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