Advanced Search
Volume 32 Issue 2
Aug.  2010
Turn off MathJax
Article Contents
Ding Rui, Gao Xi-qi, You Xiao-hu. A Revised Sequential Monte Carlo Iterative Detection for MIMO System[J]. Journal of Electronics & Information Technology, 2010, 32(2): 307-312. doi: 10.3724/SP.J.1146.2008.01801
Citation: Ding Rui, Gao Xi-qi, You Xiao-hu. A Revised Sequential Monte Carlo Iterative Detection for MIMO System[J]. Journal of Electronics & Information Technology, 2010, 32(2): 307-312. doi: 10.3724/SP.J.1146.2008.01801

A Revised Sequential Monte Carlo Iterative Detection for MIMO System

doi: 10.3724/SP.J.1146.2008.01801
  • Received Date: 2008-12-26
  • Rev Recd Date: 2009-09-28
  • Publish Date: 2010-02-19
  • An optimal iterative receiver for MIMO system need exact calculation of extrinsic information in Soft-Input-Soft-Output (SISO) detector. This optimal receiver does not fit the system with large numbers of antennas and high modulation order, because its complexity increases exponentially with modulation order and antenna number. So in this paper, the estimation of extrinsic information is proved to be equal to a choice issue of a target collection, which will be obtained by Sequential Monte Carlo (SMC) sampling. But the research also indicates that the traditional sampling method can not draw a suited target collection, so a Revised SMC (R-SMC) method is proposed to approximate a finite element discrete probability space by drawn samples. Finally, an approximate computation of extrinsic information based on R-SMC sampling is applied in this new detection algorithm. By analyses, the proposed algorithms complexity is linearly proportional to the number of drawn samples. And simulation results prove that the near-optimal Bit-Error-Ratio (BER) performance can be obtained by a small number of samples.
  • loading
  • Foschini G J. Layered Space-time architecture for wireless communication in a fading environment when using multi-element antennas [J].Bell Labs Technical Journal.1996, 1(2):41-59[2]Wang X and Poor H V. Iterative (Turbo) soft interference cancellation and decoding for coded CDMA [J].IEEE Transactions on Communications.1999, 47(7):1046-1061[3]Damen M O, Chkeif A, and Belfiore J C. Lattice code decoder for space-time codes [J].IEEE Communications Letter.2000, 4(5):161-163[4]Hochwald B M andBrink S T. Achieving near-capacity on a multiple-antenna channel [J].IEEE Transactions on Communications.2003, 51(3):389-399[5]Doucet A, Godsill S J, and Andrieu C. On sequential Monte Carlo sampling methods for Bayesian filtering [J].Statistics and Computing.2001, 10(3):197-208[6]Dong B, Wang X, and Doucet A. A new class of MIMO demodulation algorithms [J].IEEE Transactions on Signal Processing.2003, 51(11):2752-2763[7]Su Y T, Zhang X D, and Zhu X L. A low-complexity sequential Monte Carlo algorithm for blind detection in MIMO systems [J].IEEE Transactions on Signal Processing.2006, 54(7):2485-2496[8]Aggarwal P and Wang X. Multilevel sequential Monte Carlo algorithms for MIMO demodulation [J].IEEE Transactions on Wireless Communications.2007, 6(2):750-758[9]Aggarwal P, Prasad N, and Wang X. An enhanced[10]deterministic sequential Monte Carlo method for near-[11]optimal MIMO demodulation with QAM constellations [J]. IEEE Transactions on Signal Processing, 2007, 55(6): 2395-2406.[12]Yang Y, Hu J, and Zhang H. Bit-level deterministic sequential Monte Carlo method for MIMO wireless systems [C]. ICC 2008, Beijing, China, May 2008: 3622-3626.Ding R, Gao X Q, and You X H. A low-complexity implementation of sampling-based MIMO detection [C]. ICNNSP 2008, Wuxi, China, June 2008: 705-710.[13]Yee D, Reilly J P, and Kirubarajan T. A blind sequential Monte Carlo detector for OFDM systems in the presence of phase noise, multipath fading, and channel order uncertainty[J].IEEE Transactions on Signal Processing.2007, 55(9):4581-4598[14]Farhang-Boroujeny B, Zhu H, and Shi Z. Markov chain Monte Carlo algorithms for CDMA and MIMO communication systems [J].IEEE Transactions on Signal Processing.2006, 54(5):1896-1909[15]Mao X, Amini P, and Farhang-Boroujeny B. Markov chain Monte Carlo MIMO detection methods for high signal-to-noise ratio regimes [C]. GLOBECOM 2007, Washington, DC, USA, Nov. 2007: 3979-3983.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (3633) PDF downloads(893) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return