文献类型：会议论文

英文题名：Modeling for Mobile Communication Fading Channel Based on Wavelet Neural Network

作者：Gao, Meijuan[1];Tian, Jingwen[1];Zhou, Shiru[1]

第一作者：高美娟

通讯作者：Gao, MJ[1]

机构：[1]Beijing Union Univ, Dept Automat Control, Beijing, Peoples R China

第一机构：北京联合大学城市轨道交通与物流学院

通讯机构：[1]corresponding author), Beijing Union Univ, Dept Automat Control, Beijing, Peoples R China.|[1141751]北京联合大学城市轨道交通与物流学院;[11417]北京联合大学;

会议论文集：IEEE International Conference on Information and Automation

会议日期：JUN 20-23, 2008

会议地点：Changsha, PEOPLES R CHINA

语种：英文

外文关键词：Fading channels - Gradient methods - Learning algorithms

摘要：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.