Title :
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
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;
Conference_Titel :
Signal Processing and Its Applications, 2003. Proceedings. Seventh International Symposium on
Print_ISBN :
0-7803-7946-2
DOI :
10.1109/ISSPA.2003.1224633
