Title :
Neural networks for modeling nonlinear memoryless communication channels
Author :
Ibukahla, M. ; Sombria, J. ; Castanie, Francis ; Bershad, Neil J.
Author_Institution :
ENSEEIHT, Toulouse, France
fDate :
7/1/1997 12:00:00 AM
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;
Journal_Title :
Communications, IEEE Transactions on
