Blind linear channel estimation using genetic algorithm and SIMO model
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 2021-2035 |
Journal / Publication | Signal Processing |
Volume | 83 |
Issue number | 9 |
Publication status | Published - Sep 2003 |
Link(s)
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. © 2003 Elsevier B.V. All rights reserved.
Research Area(s)
- Blind channel estimation, Genetic algorithms, Second-order statistics, SIMO model
Citation Format(s)
Blind linear channel estimation using genetic algorithm and SIMO model. / Chen, Fangjiong; Kwong, Sam; Wei, Gang et al.
In: Signal Processing, Vol. 83, No. 9, 09.2003, p. 2021-2035.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review