文献类型：会议论文

英文题名：Research of wireless fading channel modeling based on radial basis function network

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

通讯作者：Jingwen, T.

机构：[1] College of Automation, Beijing Union University, Beijing, 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]College of Automation, Beijing Union University, Beijing, 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：Proceedings - 5th International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2009

会议日期：September 24, 2009 - September 26, 2009

会议地点：Beijing, China

语种：英文

外文关键词：Backpropagation - Fading channels - Functions - Learning algorithms - Least squares approximations - Mobile computing - Models - Motion compensation - Nearest neighbor search - Pattern recognition

摘要：Radial basis function network (RBFN) is one of the neural networks used widely. Aimed at the complicated and nonlinear relationship between input and output property of wireless channel and the advantages of RBFN, a method for wireless channel modeling and simulation based on RBFN is presented in this paper. We construct the structure of RBFN that used for wireless fading channel modeling, and adopt the K-Nearest Neighbor algorithm and least square method to train the network. We discussed the fading channel model and analyzed the impact factor of little-scale fading channel modeling. With the ability of strong function approach and fast convergence of RBFN, 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. ?2009 IEEE.