Implementation of a Markov Chain Monte Carlo Based Multiuser/MIMO Detector

被引:0
|
作者
Laraway, Stephen Andrew [1 ]
Farhang-Boroujeny, Behrouz [1 ]
机构
[1] Univ Utah, ECE Dept, Salt Lake City, UT 84112 USA
关键词
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Multiuser/MIMO detectors that use Markov chain Monte Carlo (MCMC) simulation techniques to obtain likelihood of information bits have been developed recently. In this paper, we explore the implementation details of one such detector and present an efficient hardware architecture of it. The first step in development of this architecture is to derive a log domain version of the Gibbs sampler, an efficient method of obtaining samples of MCMC simulator. This formulation is numerically stable and can operate with low precision. The log-domain formulation also lends itself to a hardware architecture that involves only addition, subtraction, and compare operations. Moreover, pipelining can be introduced in the proposed architecture straightforwardly. We also explore the word-length requirement of the developed architecture through computer simulations.
引用
收藏
页码:3088 / 3093
页数:6
相关论文
共 50 条
  • [21] MIMO Radar Target Localization via Markov Chain Monte Carlo Optimization
    Liang, Junli
    Chen, Yajun
    Ye, Zhonghua
    2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 2015, : 2158 - 2162
  • [22] Approaching MIMO Capacity Using Bitwise Markov Chain Monte Carlo Detection
    Chen, Rong-Rong
    Peng, Ronghui
    Ashikhmin, Alexei
    Farhang-Boroujeny, Behrouz
    IEEE TRANSACTIONS ON COMMUNICATIONS, 2010, 58 (02) : 423 - 428
  • [23] AN IMPROVED MARKOV CHAIN MONTE CARLO METHOD FOR MIMO ITERATIVE DETECTION AND DECODING
    Han Xiang Wei Jibo (Dept of Electronic Science and Engineering
    Journal of Electronics(China), 2008, (03) : 305 - 310
  • [24] Low Complexity Markov Chain Monte Carlo Detector for Channels with Intersymbol Interference
    Peng, Rong-Hui
    Chen, Rong-Rong
    Farhang-Boroujeny, Behrouz
    2009 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS, VOLS 1-8, 2009, : 1908 - 1912
  • [25] Implementation of estimating function-based inference procedures with Markov chain Monte Carlo samplers
    Tian, Lu
    Liu, Jun S.
    Wei, L. J.
    JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2007, 102 (479) : 881 - 888
  • [26] Population Markov Chain Monte Carlo
    Laskey, KB
    Myers, JW
    MACHINE LEARNING, 2003, 50 (1-2) : 175 - 196
  • [27] Monte Carlo integration with Markov chain
    Tan, Zhiqiang
    JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 2008, 138 (07) : 1967 - 1980
  • [28] Population Markov Chain Monte Carlo
    Kathryn Blackmond Laskey
    James W. Myers
    Machine Learning, 2003, 50 : 175 - 196
  • [29] Evolutionary Markov chain Monte Carlo
    Drugan, MM
    Thierens, D
    ARTIFICIAL EVOLUTION, 2004, 2936 : 63 - 76
  • [30] Markov Chain Monte Carlo in Practice
    Jones, Galin L.
    Qin, Qian
    ANNUAL REVIEW OF STATISTICS AND ITS APPLICATION, 2022, 9 : 557 - 578