Multichannel blind identification: from subspace to maximum likelihood methods

Author

Tong, Lang ; Perreau, Sylvie

Author_Institution

Sch. of Electr. Eng., Cornell Univ., Ithaca, NY, USA

Volume

86

Issue

10

fYear

1998

fDate

10/1/1998 12:00:00 AM

Firstpage

1951

Lastpage

1968

Abstract

A review of blind channel estimation algorithms is presented. From the (second-order) moment-based methods to the maximum likelihood approaches, under both statistical and deterministic signal models. We outline basic ideas behind several new developments, the assumptions and identifiability conditions required by these approaches, and the algorithm characteristics and their performance. This review serves as an introductory reference for this currently active research area

Keywords

deterministic algorithms; identification; maximum likelihood estimation; signal processing; statistical analysis; telecommunication channels; blind channel estimation algorithms; deterministic signal models; identifiability conditions; maximum likelihood methods; multichannel blind identification; performance; second-order moment-based methods; signal processing; statistical signal models; subspace methods; Blind equalizers; Computer networks; HDTV; Maximum likelihood estimation; Mobile communication; Signal processing; Signal processing algorithms; System identification; Throughput; Wireless communication;

fLanguage

English

Journal_Title

Proceedings of the IEEE

Publisher

ieee

ISSN

0018-9219

Type

jour

DOI

10.1109/5.720247

Filename

720247