Blind equalization and identification of nonlinear and IIR systems-a least squares approach

Author

Raz, Gil M. ; Van Veen, Barry D.

Author_Institution

Lincoln Lab., MIT, Lexington, MA, USA

Volume

48

Issue

1

fYear

2000

fDate

1/1/2000 12:00:00 AM

Firstpage

192

Lastpage

200

Abstract

A deterministic approach to blind nonlinear channel equalization and identification is presented. This approach applies to nonlinear channels that can be approximately linearized by either finite memory, finite-order Volterra filters, or by a finite number of finite memory nonpolynomial nonlinearities. Both the nonlinear equalizers and the linearized channels are identified. This method also applies to blind identification of linear IIR channels. General conditions for existence and uniqueness are discussed, and numerical examples are given

Keywords

IIR filters; blind equalisers; identification; least squares approximations; nonlinear filters; IIR systems; blind equalization; blind identification; blind nonlinear channel equalization; deterministic approach; existence; finite memory finite-order Volterra filters; finite memory nonpolynomial nonlinearities; identification; least squares; linear IIR channels; linearized channels; nonlinear systems; uniqueness; Blind equalizers; Convolution; Deconvolution; Finite impulse response filter; Gas insulated transmission lines; IIR filters; Least squares approximation; Least squares methods; Linear approximation; Nonlinear systems;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.815489

Filename

815489