DocumentCode :
2755930
Title :
Parameter estimation and performance evaluation of a time-varying multipath satellite channel
Author :
Rahman, Quazi Mehbubar ; Ibnkahla, M. ; Bayoumi, M.
Author_Institution :
Dept. of Eng., Saint Francis Xavier Univ., Antigonish, NS
fYear :
2005
fDate :
1-4 May 2005
Firstpage :
17
Lastpage :
20
Abstract :
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 in question 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. Both back propagation (BP) and natural gradient (NG) algorithms have been studied for the channel identification technique. 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 (the channel is perfectly known) MLSE receiver in terms of symbol error rate (SER)
Keywords :
Rician channels; backpropagation; channel allocation; channel estimation; gradient methods; maximum likelihood estimation; multipath channels; neural nets; quadrature amplitude modulation; satellite communication; telecommunication computing; time-varying channels; Doppler frequencies; QAM; Ricean-fading channel; back propagation; channel estimation method; channel identification technique; down link scenario; maximum likelihood sequence estimator; natural gradient algorithms; neural network; nonlinear time varying channel; parameter estimation; quadrature amplitude modulation; satellite channel; symbol error rate; time-varying multipath channel; AWGN; Adaptive filters; Computer networks; Finite impulse response filter; Frequency estimation; Maximum likelihood estimation; Neural networks; Nonlinear filters; Parameter estimation; Satellites;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Computer Engineering, 2005. Canadian Conference on
Conference_Location :
Saskatoon, Sask.
ISSN :
0840-7789
Print_ISBN :
0-7803-8885-2
Type :
conf
DOI :
10.1109/CCECE.2005.1556868
Filename :
1556868
Link To Document :
بازگشت