Maximum likelihood joint channel and data estimation using genetic algorithms

被引：50
|
作者：
Chen, S [1 ]
Wu, Y [1 ]
机构：
[1] Univ Portsmouth, Dept Elect & Comp Engn, Portsmouth PO1 2UP, Hants, England
来源：
IEEE TRANSACTIONS ON SIGNAL PROCESSING | 1998年 / 46卷 / 05期
关键词：
blind equalization; genetic algorithms; maximum likelihood estimation;
D O I：
10.1109/78.668813
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
A batch blind equalization scheme is developed based on maximum likelihood joint channel and data estimation. In this scheme, the joint maximum likelihood optimization is decomposed into a two-level optimization loop. A micro genetic algorithm is employed at the upper level to identify the unknown channel model, and the Viterbi algorithm is used at the lower level to provide the maximum likelihood sequence estimation of the transmitted data sequence. As is demonstrated in simulation, the proposed method is much more accurate compared with existing algorithms for joint channel and data estimation.
引用
收藏
页码：1469 / 1473
页数：5
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