Blind Identification of Multichannel Systems by Scalar-Valued Linear Prediction

Shuichi OHNO  Hideaki SAKAI  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E84-A   No.8   pp.1856-1862
Publication Date: 2001/08/01
Online ISSN: 
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Digital Signal Processing)
Category: Adaptive Signal Processing
multichannel,  blind identification,  subspace method,  

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An algorithm for blind identification of multichannel (single-input and multiple-output) FIR systems is proposed. The proposed algorithm is based on subspace approach to blind identification, which requires so-called noise space spanned by some eigenvectors of correlation matrices of observations. It is shown that a subspace of the noise space can be obtained by one-step scalar-valued linear prediction and then the subspace is sufficient for blind identification. To acquire the subspace, the proposed algorithm utilizes one-step scalar-valued linear prediction in place of a singular- (or eigen-) value decomposition and hence it is computationally efficient. Computer simulations are presented to compare the proposed algorithm with the original one.