A neural network MLSE receiver based on natural gradient descent: application to satellite communications

Author

Ibnkahla, Mohamed ; Yuan, Jun

Author_Institution

Dept. of Electr. & Comput. Eng., Queen´´s Univ., Kingston, Ont., Canada

Volume

1

fYear

2003

fDate

1-4 July 2003

Firstpage

33

Abstract

The paper proposes a maximum likelihood sequence estimator (MLSE) receiver for satellite communications. The satellite channel model is composed of a nonlinear traveling wave tube (TWT) amplifier followed by a multipath propagation channel. The receiver is composed of a neural network channel estimator (NNCE) and a Viterbi detector. The natural gradient (NG) descent is used for training. Computer simulations show that the performance of our receiver is close to the ideal MLSE receiver in which the channel is perfectly known.

Keywords

Viterbi detection; channel estimation; maximum likelihood sequence estimation; multipath channels; neural nets; receivers; satellite communication; travelling wave amplifiers; MLSE; TWT; Viterbi detector; maximum likelihood sequence estimator receiver; multipath propagation channel; natural gradient descent; neural network channel estimator; nonlinear traveling wave tube amplifier; satellite channel model; satellite communications; Adaptive filters; Application software; Computer simulation; Detectors; Maximum likelihood estimation; Neural networks; Nonlinear distortion; Nonlinear filters; Phase modulation; Satellite communication;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Its Applications, 2003. Proceedings. Seventh International Symposium on

Print_ISBN

0-7803-7946-2

Type

conf

DOI

10.1109/ISSPA.2003.1224633

Filename

1224633