EURASIP Journal on Advances in Signal Processing 
Volume 2008 (2008), Article ID 960295, 9 pages
doi:10.1155/2008/960295
Research Article

Blind Channel Equalization with Colored Source Based on Constrained Optimization Methods

Yunhua Wang,1 Linda DeBrunner,1 Victor DeBrunner,1 and Dayong Zhou2

 1Department of Electrical and Computer Engineering, Oklahoma University, Norman, OK 73072, USA
2Cirrus Logic Inc., 2901 Via Fortuna, Austin, TX 78746, USA
Received 20 February 2008; Revised 23 June 2008; Accepted 11 September 2008

Recommended by Magnus Jansson

Abstract

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.