DocumentCode :
1749122
Title :
UMTS channel equalization using neural networks: natural gradient algorithm
Author :
Abdulkader, H. ; Langlet, F. ; Roviras, D. ; Castanie, F.
Author_Institution :
ENSEEIHT, Toulouse, France
Volume :
1
fYear :
2001
fDate :
2001
Firstpage :
699
Abstract :
Neural networks (NN) have been widely used in adaptive signal processing last decade. Their adaptive properties and nonlinear characteristics make them powerful tools to overcome difficult nonlinear problems. Satellite communications channels have nonlinear complex gain which makes the decision boundaries between different symbols nonlinear. NNs have been successfully used for satellite channel equalization. In this paper we present a multilayer neural network equalizer applied to UMTS channel equalization. We propose to use the natural gradient algorithm instead of the ordinary gradient in order to enhance the convergence properties of the NN
Keywords :
channel allocation; equalisers; gradient methods; mobile satellite communication; multilayer perceptrons; telecommunication computing; UMTS channel equalization; adaptive properties; adaptive signal processing; convergence properties; decision boundaries; multilayer neural network equalizer; natural gradient algorithm; nonlinear characteristics; nonlinear complex gain; satellite channel equalization; satellite communications channels; 3G mobile communication; Adaptive signal processing; Digital communication; Equalizers; Filters; High power amplifiers; Multi-layer neural network; Neural networks; Satellite communication; Signal processing algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
ISSN :
1098-7576
Print_ISBN :
0-7803-7044-9
Type :
conf
DOI :
10.1109/IJCNN.2001.939109
Filename :
939109
Link To Document :
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