Equivariant blind deconvolution of MIMO-FIR channels

Author

Gorokhov, Alexei ; Cardoso, Jean-FranGois

Author_Institution

Dept. Signal, CNRS, Paris, France

fYear

1997

fDate

16-18 April 1997

Firstpage

89

Lastpage

92

Abstract

We address the blind identification and deconvolution of multiple input multiple output (MIMO) linear FIR channels. This is an instance of blind separation of convolutive mixtures. The unknown system is decomposed in two factors. The first factor can be deterministically identified from a finite data set; the second factor is shown to belong to a multiplicative group. This last property allows the implementation of effective equivariant deconvolution algorithms, including the maximum likelihood (ML) estimator.

Keywords

FIR filters; MIMO systems; deconvolution; maximum likelihood estimation; telecommunication channels; uncertain systems; MIMO-FIR channels; blind identification; blind separation; convolutive mixtures; decomposition; effective equivariant deconvolution algorithms; equivariant blind deconvolution; finite data set; maximum likelihood estimator; multiple input multiple output linear FIR channels; multiplicative group; unknown system; Data models; Deconvolution; Equations; Finite impulse response filter; MIMO; Maximum likelihood estimation; Reduced order systems; Signal processing; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Advances in Wireless Communications, First IEEE Signal Processing Workshop on

Conference_Location

Paris, France

Print_ISBN

0-7803-3944-4

Type

conf

DOI

10.1109/SPAWC.1997.630076

Filename

630076