The Research of the Complex-valued Blind Equalization Algorithm Beased on the Feedforward Neural Network
Xiaoqin Zhang · Journal of Taiyuan University of Technology · 2006
In this paper,a new complex-valued blind equalization algorithm based on the feedforward neural network(N-FNN) is proposed.Because the traditional equalization technology requests to transmit the training sequence constantly,the effective information rate of the system is low.The new algorithm has changed this status.It can eliminate Intersymbol Interference(ISI) effectively and improve the communication quality.The new transmission function and cost function are designed in this paper.At the same time,weight iteration formula of the output layer and hidden layer are deduced using the steepest descent method.Results of the simulation for QAM signals show that the proposed algorithm has faster mean square error convergence speed,and lower bit error rate,smaller steady state mean square error than the other similar algorithms.