Blind Channel Identification Based on Eigenvalue Decomposition Using Constrained LMS Algorithm

Kyung Seung AHN  Eul Chool BYUN  Heung Ki BAIK  

Publication
IEICE TRANSACTIONS on Communications   Vol.E85-B   No.5   pp.961-966
Publication Date: 2002/05/01
Online ISSN: 
DOI: 
Print ISSN: 0916-8516
Type of Manuscript: Special Section LETTER (Wireless Communications Issue)
Category: 
Keyword: 
blind channel estimation,  constrained LMS,  eigenvalue decomposition,  

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Summary: 
Blind adaptive channel identification of communication channels is a problem of important current theoretical and practical concerns. Recently proposed solutions for this problem exploit the diversity induced by antenna array or time oversampling, leading to the so-called, second order statistics techniques. Adaptive blind channel identification techniques based on a off-line least-squares approach have been proposed but this method assumes noise-free case. The method resorts to an adaptive filter with a linear constraint. This paper proposes a new approach based on eigenvalue decomposition. Indeed, the eigenvector corresponding to the minimum eigenvalue of the covariance matrix of the received signals contains the channel impulse response. And we present a adaptive algorithm to solve this problem. The performance of the proposed technique is evaluated over real measured channel and is compared to existing algorithms.