Wireless Channel Model Based on RBF Neural Network

According to the actual wireless channel can be considered as a nonlinear transmission system, and radial basis function (RBF) neural network has fitly favorable performance in simulating nonlinear system and prestissimo learning speed without local infinitesimal value, and can approach any arbitrary nonlinear function with any precision. So this paper proposes a wireless communication channel model based on RBF neural network. In this paper, a modeling method is studied, and three kinds of channels are simulated. Simulation results show that the RBF neural network model has a nicer effect on approaching wireless communication channel. It can track the time-varying characteristic of wireless channels better with very small error, can reduce the complicated calculation of wireless channel and directly extract useful channel information.