A Novel Blind Channel Identification and Equalisation Algorithm Based on Maximum Likelihood

被引:4
|
作者
Lakkis I. [1 ,3 ,4 ,5 ,6 ,10 ]
Mclernon D. [2 ,5 ,7 ,8 ,9 ,10 ,11 ]
Lopes L. [5 ,10 ,12 ,13 ,14 ,15 ]
机构
[1] Wireless Facilities Inc., 9725 Scranton RD, San Diego
[2] Dept. of Electron. and Elec. Eng., University of Leeds
[3] Wireless Facilities Inc., San Diego, CA
[4] Department of Electrical Engineering, Queen's University, Belfast
[5] Imperial College, London University
[6] South Bank University, London
[7] Electron. and Elec. Eng. Department, University of Leeds
[8] GSM Reserach Group, Motorola
基金
英国工程与自然科学研究理事会;
关键词
Blind equalisation; Cyclostationarity; FIR channel identification; Maximum likelihood; Music algorithm;
D O I
10.1023/A:1008880608792
中图分类号
学科分类号
摘要
A novel blind non-decision directed maximum likelihood algorithm for fractionally-spaced nonminimum phase FIR channel identification and equalisation is presented. The algorithm results from using the low signal to noise approximation to the average of the likelihood function with respect to the transmitted data sequence. The channel estimation equation is derived in a closed form. The resulting algorithm has two distinct advantages. The first is that the channel estimates are asymptotically consistent, and the second is that the algorithm is computationally efficient since it only requires the calculation of one eignevector. Simulation results are presented to show the performance of the proposed algorithm.
引用
收藏
页码:73 / 92
页数:19
相关论文
共 50 条
  • [1] Unconditional maximum likelihood channel estimation and equalisation
    Lakkis, I
    McLernon, D
    FIRST IEEE SIGNAL PROCESSING WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS, 1997, : 17 - 20
  • [2] Sign algorithm for blind channel equalisation
    Abrar, S.
    ELECTRONICS LETTERS, 2016, 52 (07) : 527 - 528
  • [3] Blind equalisation using approximate maximum likelihood source separation
    Choi, S
    Cichocki, A
    ELECTRONICS LETTERS, 2001, 37 (01) : 61 - 62
  • [4] An eigenanalysis-based method for blind channel identification and equalisation
    Chen, SP
    Yao, TR
    EUROPEAN TRANSACTIONS ON TELECOMMUNICATIONS, 2005, 16 (04): : 349 - 355
  • [5] Training based maximum likelihood channel identification
    Rousseaux, O
    Leus, G
    Stoica, P
    Moonen, M
    2003 4TH IEEE WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS - SPAWC 2003, 2004, : 334 - 338
  • [6] Blind channel identification and equalisation in OFDM using subspace-based methods
    Alayyan, Faisal O.
    Shubair, Raed M.
    Zoubir, Abdelhak M.
    Leung, Yee Hong
    Journal of Communications, 2009, 4 (07): : 472 - 484
  • [7] Novel DWPM system based on ML algorithm and blind channel identification
    Zhou, Lei
    Li, Jian-Dong
    Chen, Chen
    Li, Feng
    Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology, 2005, 27 (08): : 1254 - 1257
  • [8] Blind maximum likelihood identification of Hammerstein systems
    Vanbeylen, Laurent
    Pintelon, Rik
    Schoukens, Johan
    AUTOMATICA, 2008, 44 (12) : 3139 - 3146
  • [9] The development of blind equalization algorithm based on maximum likelihood sequence estimation
    Chen, X
    Bai, YQ
    Zhang, LY
    ISTM/2005: 6th International Symposium on Test and Measurement, Vols 1-9, Conference Proceedings, 2005, : 8450 - 8453
  • [10] Log-likelihood adaptive algorithm in single-layer perceptron based channel equalisation
    Shang, C.
    Holt, M.J.J.
    Cowan, C.F.N.
    Electronics Letters, 1995, 31 (22): : 1900 - 1902