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.

Additional Metadata
Keywords Frequency-selective fading, Neural networks, Satellite communications
Conference Proceedings of the IASTED International Conference on Neural Networks and Computational Intelligence
Citation
Ibnkahla, M, & Yuan, J. (2003). Neural network MLSE receiver for satellite channels in the presence of nonlinear distortions and frequency-selective fading. In Proceedings of the IASTED International Conference on Neural Networks and Computational Intelligence (pp. 157–162).