DocumentCode
2702433
Title
Modeling for mobile communication fading channel based on wavelet neural network
Author
Gao, Meijuan ; Tian, Jingwen ; Zhou, Shiru
Author_Institution
Dept. of Autom. Control, Beijing Union Univ., Beijing
fYear
2008
fDate
20-23 June 2008
Firstpage
1566
Lastpage
1570
Abstract
Aimed at the complicated and nonlinear relationship between input and output property of wireless channel and the advantages of wavelet neural network (WNN), a method for wireless channel modeling and simulation based on WNN is presented in this paper. Moreover, we adopt an algorithm of reduce the number of the wavelet basic function by analysis the sparse property of sample data which can optimize the wavelet network in a large extent, and the learning algorithm based on the gradient descent was used to train network. We discussed the fading channel model and analyzed the impact factor of little-scale fading channel modeling. With the ability of strong nonlinear function approach and fast convergence rate of WNN, the modeling method can implement the modeling and simulation of fading channel rapidly and effectively by learning the propagation characteristic information of wireless channel. The simulation result shows the feasibility and validity of modeling method.
Keywords
fading channels; gradient methods; learning (artificial intelligence); mobile communication; neural nets; nonlinear functions; telecommunication computing; wavelet transforms; gradient descent method; learning algorithm; mobile communication fading channel; nonlinear function approach; wavelet basic function; wavelet neural network; wireless channel modeling; wireless channel simulation; Artificial neural networks; Convergence; Electromagnetic modeling; Electromagnetic propagation; Fading; Frequency; Mathematical model; Mobile communication; Neural networks; Wavelet analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Information and Automation, 2008. ICIA 2008. International Conference on
Conference_Location
Changsha
Print_ISBN
978-1-4244-2183-1
Electronic_ISBN
978-1-4244-2184-8
Type
conf
DOI
10.1109/ICINFA.2008.4608252
Filename
4608252
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