DocumentCode :
2136016
Title :
A pilot-aided neural network for modeling and identification of nonlinear satellite mobile channels
Author :
Ibnkahla, Mohamed ; Cao, Yu
Author_Institution :
Electr. & Comput. Eng. Dept., Queen´´s Univ., Kingston, ON
fYear :
2008
fDate :
4-7 May 2008
Abstract :
We propose a neural network pilot symbol-aided (NN-PSA) receiver for nonlinear satellite mobile channels. The NN-PSA receiver is composed of a two-layer memory-less neural network (NN) nonlinear identifier and a pilot symbol-aided (PSA) fading estimator. In comparison with traditional techniques, the main advantage of this receiver is that it is able to identify and track both the nonlinearity and the time-varying fading simultaneously without prior knowledge of them. The natural gradient (NG) descent is used for NN training, which shows superior performance in comparison to the classical back propagation (BP) algorithm. The paper is supported with simulation results for 16-QAM modulation in terms of symbol error rate (SER) and mean square error (MSE) performance.
Keywords :
fading channels; gradient methods; mean square error methods; mobile satellite communication; neural nets; mean square error; memoryless neural network nonlinear identifier; natural gradient descent; neural network pilot symbol-aided receiver; nonlinear satellite mobile channels; pilot symbol-aided fading estimator; symbol error rate; time-varying fading; Computer networks; Downlink; Fading; High power amplifiers; Mobile computing; Neural networks; Nonlinear dynamical systems; Satellites; Telephony; Transmitters; MIMO systems; Neural networks; satellite communications;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Computer Engineering, 2008. CCECE 2008. Canadian Conference on
Conference_Location :
Niagara Falls, ON
ISSN :
0840-7789
Print_ISBN :
978-1-4244-1642-4
Electronic_ISBN :
0840-7789
Type :
conf
DOI :
10.1109/CCECE.2008.4564800
Filename :
4564800
Link To Document :
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