A Novel MCMC Algorithm for Near-Optimal Detection in Large-Scale Uplink Mulituser MIMO Systems

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In this paper, the authors propose a low-complexity algorithm based on Markov Chain Monte Carlo (MCMC) technique for signal detection on the uplink in large scale multiuser Multiple Input Multiple Output (MIMO) systems with tens to hundreds of antennas at the Base Station (BS) and similar number of uplink users. The algorithm employs a randomized sampling method (which makes a probabilistic choice between Gibbs sampling and random sampling in each iteration) for detection. The proposed algorithm alleviates the stalling problem encountered at high SNRs in conventional MCMC algorithm and achieves near-optimal performance in large systems with M-QAM.