OFDM Channel Prediction Using Fuzzy Update LMS Algorithm in Time-Variant Mobile Channel

Abstract

Channel predictor implemented by discrete Fourier transform (DFT) is considered, which predict the channel gain of each receiving path by adaptive filters. A fuzzy logic controlled step size could overcome the drawback of conventional least-mean-square error (LMS) algorithm. In this paper, LMS algorithm with fuzzy updated step size is proposed to realize the adaptive channel prediction in orthogonal frequency division multiplexing (OFDM) systems. Simulation results show that as compared to conventional LMS algorithm, the proposed algorithm can achieve a faster convergence rate and lower steady-state mean square error. The proposed algorithm can also achieve more robust tracking ability in the various channel environments.