Neural networks for modeling nonlinear memoryless communication channels

Author

Ibukahla, M. ; Sombria, J. ; Castanie, Francis ; Bershad, Neil J.

Author_Institution

ENSEEIHT, Toulouse, France

Volume

45

Issue

7

fYear

1997

fDate

7/1/1997 12:00:00 AM

Firstpage

768

Lastpage

771

Abstract

This paper presents a neural network approach for modeling nonlinear memoryless communication channels. In particular, the paper studies the approximation of the nonlinear characteristics of traveling-wave tube (TWT) amplifiers used in satellite communications. The modeling is based upon multilayer neural networks, trained by the odd and even backpropagation (BP) algorithms. Simulation results demonstrate that neural network models fit the experimental data better than classical analytical TWT models,

Keywords

backpropagation; electric distortion; memoryless systems; multilayer perceptrons; satellite communication; telecommunication channels; telecommunication computing; travelling wave amplifiers; travelling wave tubes; AM/AM conversion; AM/PM conversion; TWT amplifiers; amplitude distortion; channel modeling; even backpropagation algorithm; experimental data; multilayer neural networks; neural network models; nonlinear characteristics approximation; nonlinear memoryless communication channels; odd backpropagation algorithm; phase distortion; satellite communications; simulation results; traveling-wave tube amplifiers; Analytical models; Backpropagation algorithms; Communication channels; Frequency; Multi-layer neural network; Neural networks; Nonlinear distortion; Performance analysis; Phase distortion; Satellite communication;

fLanguage

English

Journal_Title

Communications, IEEE Transactions on

Publisher

ieee

ISSN

0090-6778

Type

jour

DOI

10.1109/26.602580

Filename

602580