A globally convergent approach for blind MIMO adaptive deconvolution

Author

Touzni, A. ; Fijalkow, I. ; Larimore, M. ; Treichler, J.R.

Author_Institution

CNRS, Cergy-Pontoise, France

Volume

4

fYear

1998

fDate

12-15 May 1998

Firstpage

2385

Abstract

We address the deconvolution of MIMO linear mixtures. The approach is based on the construction of a hierarchical family of composite criteria involving CM criterion and second order statistics constraint. Although, the criteria are based on fourth order statistics, we give a complete proof of convergence of this structure. We show that each cost function leads to the restoration of one single source. Moreover the approach is naturally robust with respect to the channels order estimation. An adaptive algorithm is derived for the simultaneous estimation of all sources

Keywords

MIMO systems; adaptive signal processing; convergence of numerical methods; deconvolution; higher order statistics; signal restoration; stochastic processes; MIMO linear mixtures; blind MIMO adaptive deconvolution; channel order estimation; constant modulus criterion; convergence; cost function; fourth order statistics; globally convergent approach; hierarchical composite criteria; second order statistics constraint; source estimation; source restoration; stochastic adaptive algorithm; Adaptive signal processing; Convergence; Costs; Deconvolution; MIMO; Robustness; Signal restoration; Source separation; Statistics; Wireless communication;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on

Conference_Location

Seattle, WA

ISSN

1520-6149

Print_ISBN

0-7803-4428-6

Type

conf

DOI

10.1109/ICASSP.1998.681630

Filename

681630