Blind linear channel estimation using genetic algorithm and SIMO model

Fangjiong CHEN, Sam KWONG, Gang WEI, Cleve K.W. KU, K. F. MAN

Research output: Journal PublicationsJournal Article (refereed)peer-review

13 Citations (Scopus)


In this paper, we propose to use genetic algorithm (GA) to solve the blind infinite-impulse-response (IIR) channel estimation problem. The contributions of this paper are three-fold: (1) We prove that by oversampling the output of a single-input-single-output IIR channel, one can build a single-input-multiple-output (SIMO) model in which the subchannels are IIR channels with the same Autoregressive (AR) order and coefficients. (2) Based on this SIMO model, we further develop a second-order statistics based objective function that includes the unknown model order and parameters whereas most of the existing work must assume the channel order is known in advance. (3) A GA is proposed to deal with this optimisation problem in that we encode the model order and parameters into one single chromosome. Therefore the order and parameters can be estimated simultaneously. Computer simulation results indicate the effectiveness of the proposed algorithms. © 2003 Elsevier B.V. All rights reserved.
Original languageEnglish
Pages (from-to)2021-2035
JournalSignal Processing
Issue number9
Publication statusPublished - Sept 2003
Externally publishedYes

Bibliographical note

This work is supported by City University Strategic grant 7001337.


  • Blind channel estimation
  • Genetic algorithms
  • Second-order statistics
  • SIMO model


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