Blind linear channel estimation using genetic algorithm and SIMO model

  • Authors:

  • Fangjiong Chen;Sam Kwong;Gang Wei;Cleve K. W. Ku;K. F. Man

  • Affiliations:

  • Department of Electronic Engineering, South China University of Technology, Guangzhou, P.R. China and Department of Computer Science, City University of Hong Kong, 83 Tatchee Ave, Kowloon, Hong Ko ...;Department of Computer Science, City University of Hong Kong, 83 Tatchee Ave, Kowloon, Hong Kong;Department of Electronic Engineering, South China University of Technology, Guangzhou, P.R. China;Department of Computer Science, City University of Hong Kong, 83 Tatchee Ave, Kowloon, Hong Kong;Department of Electronic Engineering, City University of Hong Kong, Hong Kong

  • Venue:
  • Signal Processing
  • Year:
  • 2003

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Abstract

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.