Blind equalization of a noisy channel by linear neural network

Author

Fang, Yong ; Chow, Tommy W S

Author_Institution

Dept. of Electron. Eng., City Univ. of Hong Kong, Hong Kong

Volume

10

Issue

4

fYear

1999

fDate

7/1/1999 12:00:00 AM

Firstpage

918

Lastpage

924

Abstract

In this paper, a new neural approach is introduced for the problem of blind equalization in digital communications. Necessary and sufficient conditions for blind equalization are proposed, which can be implemented by a two-layer linear neural network, in the hidden layer, the received signals are whitened, while the network outputs provide directly an estimation of the source symbols. We consider a stochastic approximate learning algorithm for each layer according to the property of the correlation matrices of the transmitted symbols. The proposed class of networks yield good results in simulation examples for the blind equalization of a three-ray multipath channel

Keywords

blind equalisers; correlation methods; digital communication; learning (artificial intelligence); multilayer perceptrons; multipath channels; stochastic processes; blind equalization; correlation matrices; digital communications; hidden layer; necessary and sufficient conditions; noisy channel; signal whitening; stochastic approximate learning algorithm; three-ray multipath channel; two-layer linear neural network; Adaptive equalizers; Blind equalizers; Deconvolution; Delay estimation; Digital communication; Intersymbol interference; Multipath channels; Neural networks; Stochastic processes; Sufficient conditions;

fLanguage

English

Journal_Title

Neural Networks, IEEE Transactions on

Publisher

ieee

ISSN

1045-9227

Type

jour

DOI

10.1109/72.774261

Filename

774261