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

Authors:
Mohamed Ibnkahla;Jun Yuan
Affiliations:
Electrical and Computer Engineering Department, Queen's University, Kingston, Ontario, Canada;Electrical and Computer Engineering Department, Queen's University, Kingston, Ontario, Canada
Venue:
EURASIP Journal on Applied Signal Processing
Year:
2004

Citing 12
Cited 2

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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.