In wireless channel modeling and simulation， it is of great significance to realize a high-efficiency and high-accuracy wireless channel prediction method. Aiming at this request， a wireless channel prediction method based on multi-population genetic algorithm-back propagation （MPGA-BP） neural network is proposed. This method optimizes the structure parameters of BP neural network by improving the genetic algorithm， thereby improving the problem of poor prediction accuracy of the BP neural network and greatly improving the prediction performance of the BP neural network. In this paper， the theoretical value of ray tracing algorithm is combined with BP neural network to realize a more efficient wireless channel prediction method. By comparing the prediction errors of the genetic algorithm （GA）-BP neural network model and the MPGA-BP neural network model， it is found that the prediction results of the MPGA-BP neural network model are better than the GA-BP neural network model， which proves that the proposed wireless channel prediction method has good accuracy. Therefore， the wireless channel prediction can be performed more efficiently.