tailieunhanh - Báo cáo hóa học: " Research Article Blind Channel Equalization with Colored Source Based on Constrained Optimization Methods"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Blind Channel Equalization with Colored Source Based on Constrained Optimization Methods | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 960295 9 pages doi 2008 960295 Research Article Blind Channel Equalization with Colored Source Based on Constrained Optimization Methods Yunhua Wang 1 Linda DeBrunner 2 Victor DeBrunner 2 and Dayong Zhou3 1 Department of Electrical and Computer Engineering Oklahoma University Norman OK 73072 USA 2 Department of Electrical and Computer Engineering Florida State University Tallahassee FL 32306 USA 3 Cirrus Logic Inc. 2901 Via Fortuna Austin TX 78746 USA Correspondence should be addressed to Dayong Zhou dayong@ Received 20 February 2008 Revised 23 June 2008 Accepted 11 September 2008 Recommended by Magnus Jansson 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. Copyright 2008 Yunhua Wang et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and .