Channel Estimation of RBF Networks Based on Improved Genetic Algorithm Optimization
In order to improve the accuracy of channel estimation in communication systems and adapt to larger data for more complex data calculation,a neural network method was introduced for channel estimation.Experiment comparsion is conducted be-tween the radial basis function(RBF)neural network and back propagation(BP)neural network,compared with traditional channel estimation methods,the experimental results show significant improvement.On this basis,an RBF neural channel estimation method based on improved genetic algorithm was also proposed.The purpose is to determine the hidden layer parameters of RBF network,making the network parameters to the universally optimal solution,and then improving the efficacy of the channel estimator.The en-hanced RBF neural network effectively resolve the channel estimation by MATLAB simulation,thereby verifying the feasibility of this approach.
orthogonal frequency division multiplexing(OFDM)systemgenetic algorithmRBF neural networkchannel esti-matorMatlab
万方数据
维普
