Channel Estimation For OFDM Systems In Time-varying Channels

In mobile communication systems, Orthogonal Frequency Division Multiplexing is a special multicarrier modulation technique with several desirable features, e.g. robutness against multipath propagation and high spectral efficiency. OFDM is increasingly used in high-mobility communication systems. Howevr, communication systems using multicarrier modulation schemes over selective channels are affected by interference (ICI). And in time-varying channels, the system model is no longer constant. So it is neccesiry to estimate communication channels to get the object of improving the performance of the whole sysytems.This paper mainly study time-varing estimation in OFDM systems. Research results are mainly embodied in tow aspects.1. In varying environments, the traditional estimation method was poor in performance and high in computational complexity for SISO-OFDM systems. In order to solve this problem, we proposed a novel method named dual-diagonal LMMSE. First we set up the system model based on the basis expansion model (BEM). Then the estimated coefficients of BEM by taking twice diagonal LMMSE were used to recovery the channel impulse response (CIR) in the time domain. The simulation results show that the proposed method achieves better performance and lower computational complexity in fast varying environment.2. In varying environments, extended kalman filtering method is lower in precious on nonlinear filtering estimation for MIMO-OFDM systems. We proposed the modified particle filtering method. Though introducing distance comparing and optimized combination, the proposed method overcomes common problems in traditional particle filtering, namely, the problems of particles diversity loss and the abandoning the worthy particle after resampling. As a result, the method can express the posterior PDF of the state more accurately and improves the estimating accuracy. The simulation results verify that the presented method is efficient.