NDLI: Markov Chain Monte Carlo: Applications to MIMO detection and channel equalization

Content Provider	IEEE Xplore Digital Library
Author	Rong-Rong Chen Ronghui Peng Farhang-Boroujeny, B.
Copyright Year	2009
Description	Author affiliation: Department of Electrical and Computer Eng., University of Utah, Salt Lake City, 84093, USA (Rong-Rong Chen; Ronghui Peng; Farhang-Boroujeny, B.)
Abstract	In this paper, we present an overview of recent work on the applications of Markov Chain Monte Carlo (MCMC) techniques to both multiple-input and multiple-output (MIMO) detection and channel equalization. In the setting of MIMO detection, we have shown that, even for very large antenna systems with high spectral efficiencies of 24 bits/channel use (8 transmit and 8 receive antennas with 64 QAM modulation), the MCMC MIMO detector can bring us within 2 dB of the channel capacity with a greatly reduced complexity compared to several versions of sphere decoding based detectors. For frequency selective channels, we demonstrate that MCMC-based equalizers yield excellent performance even for severe inter-symbol-interference (ISI) channels. The MCMC equalizer achieves significant performance gain over minimum mean square error (MMSE) linear equalizer and performs closely to the optimal maximum a posteriori probability (MAP) equalizer. We will also discuss new approaches that effectively alleviate the well-known high SNR problems in existing MCMC detectors.
Starting Page	44
Ending Page	49
File Size	909039
Page Count	6
File Format	PDF
ISBN	9781424439904
DOI	10.1109/ITA.2009.5044921
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-02-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Monte Carlo methods Equalizers Quadrature amplitude modulation Channel capacity Transmitting antennas Receiving antennas Detectors Frequency MIMO Decoding
Content Type	Text
Resource Type	Article

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