Open Access

Blind Channel Equalization with Colored Source Based on Constrained Optimization Methods

  • Yunhua Wang1,
  • Linda DeBrunner2,
  • Victor DeBrunner2 and
  • Dayong Zhou3Email author
EURASIP Journal on Advances in Signal Processing20082008:960295

Received: 20 February 2008

Accepted: 11 September 2008

Published: 28 October 2008


Tsatsanis and Xu have applied the constrained minimum output variance (CMOV) principle to directly blind equalize a linear channel—a technique that has proven effective with white inputs. It is generally assumed in the literature that their CMOV method can also effectively equalize a linear channel with a colored source. In this paper, we prove that colored inputs will cause the equalizer to incorrectly converge due to inadequate constraints. We also introduce a new blind channel equalizer algorithm that is based on the CMOV principle, but with a different constraint that will correctly handle colored sources. Our proposed algorithm works for channels with either white or colored inputs and performs equivalently to the trained minimum mean-square error (MMSE) equalizer under high SNR. Thus, our proposed algorithm may be regarded as an extension of the CMOV algorithm proposed by Tsatsanis and Xu. We also introduce several methods to improve the performance of our introduced algorithm in the low SNR condition. Simulation results show the superior performance of our proposed methods.

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Authors’ Affiliations

Department of Electrical and Computer Engineering, Oklahoma University
Department of Electrical and Computer Engineering, Florida State University
Cirrus Logic Inc.


© Yunhua Wang et al. 2008

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.