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Neural network based channel estimation and performance evaluation of time varying multipath satellite channel

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3 Author(s)
Rahman, Q.M. ; Dept. of Eng., St. Francis Xavier Univ., Antigonish, NS, Canada ; Ibnkahla, M. ; Bayoumi, M.M.

Neural network (NN) based channel estimation method has been proposed for identifying the parameters of a nonlinear time varying satellite channel. A multipath time-varying Ricean-fading channel has been considered in the analysis for a down link scenario. To study the flexibility and performance of the proposed method, the channel has been varied over a reasonable range of Doppler frequencies, and the estimation for each case has been made by employing 16-quadrature amplitude modulation (16-QAM) technique. Back propagation (BP) and natural gradient (NG) algorithms have been studied for the channel identification technique. Based on different learning rates and normalized Doppler frequencies, a comparative analysis between the algorithms has been provided. Finally, a NN maximum likelihood sequence estimator (NN-MLSE) based receiver has been studied for the addressed system. Simulation results show that the NN-MLSE receiver performs close to that of the ideal MLSE receiver in terms of symbol error rate (SER).

Published in:

Communication Networks and Services Research Conference, 2005. Proceedings of the 3rd Annual

Date of Conference:

16-18 May 2005