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In order to improve the accuracy of channel estimation in communication systems and adapt to larger data volumes for more complex data calculations, a neural network method was introduced for channel estimation. An RBF neural network and a BP neural network were harnessed for an experimental comparison, demonstrating a notable enhancement over conventional channel estimation techniques. Building on this, an RBF neural channel estimation method optimized by a genetic algorithm was also suggested. This is intended to assist in establishing the hidden layer parameters of the RBF network, steering the network parameters toward the universally optimal solution and thereby boosting the efficacy of the channel estimator.The enhanced RBF neural network"s capability to effectively resolve the channel estimation issue is confirmed by the MATLAB simulation, thereby demonstrating the viability of this approach.