Vector neural networks for digital satellite communications

Author

Ibnkahla, M. ; Castanie, F.

Author_Institution

ENSEEIHT, Toulouse, France

Volume

3

fYear

1995

fDate

18-22 Jun 1995

Firstpage

1865

Abstract

Conventional techniques used for identification and equalization of nonlinear M-ary PSK digital satellite channels are based on linear or nonlinear filtering devices (e.g. tapped delay line equalizers, Volterra series approaches). This paper uses a new technique based on the vector neural network (VNN) and Kohonen (1989) self organizing feature map. We have used a VNN for adaptive equalization and identification of the satellite channel. The decision process is performed by a Kohonen map

Keywords

adaptive equalisers; backpropagation; digital radio; identification; phase shift keying; satellite communication; self-organising feature maps; telecommunication channels; telecommunication computing; Kohonen self organizing feature map; adaptive equalization; adaptive identification; decision process; digital satellite channels; digital satellite communications; nonlinear M-ary PSK; vector neural networks; Delay lines; Digital filters; Equalizers; Filtering; Neural networks; Nonlinear filters; Organizing; Phase shift keying; Satellite communication; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications, 1995. ICC '95 Seattle, 'Gateway to Globalization', 1995 IEEE International Conference on

Conference_Location

Seattle, WA

Print_ISBN

0-7803-2486-2

Type

conf

DOI

10.1109/ICC.1995.524521

Filename

524521