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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.