NDLI: A novel MCMC algorithm for near-optimal detection in large-scale uplink mulituser MIMO systems

Content Provider	IEEE Xplore Digital Library
Author	Datta, T. Ashok Kumar, N. Chockalingam, A. Sundar Rajan, B.
Copyright Year	2012
Description	Author affiliation: Department of ECE, Indian Institute of Science, Bangalore-560012, India (Datta, T.; Ashok Kumar, N.; Chockalingam, A.; Sundar Rajan, B.)
Abstract	In this paper, we 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. A novel ingredient in the algorithm that is responsible for achieving near-optimal performance at low complexities is the joint use of a randomized MCMC (R-MCMC) strategy coupled with a multiple restart strategy with an efficient restart criterion. Near-optimal detection performance is demonstrated for large number of BS antennas and users (e.g., 64, 128, 256 BS antennas/users).
Starting Page	69
Ending Page	77
File Size	230126
Page Count	9
File Format	PDF
ISBN	9781467314732
e-ISBN	9781467314725
DOI	10.1109/ITA.2012.6181816
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-02-05
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	detection Quadrature amplitude modulation multiple restarts randomized sampling Bit error rate Vectors stalling problem Complexity theory Decoding Markov chain Monte Carlo technique Gibbs sampling Receiving antennas Large-scale multiuser MIMO MIMO
Content Type	Text
Resource Type	Article

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