LAUSR

The acquisition of channel state information (CSI) is a vital and challenging task in wireless communications, especially for high mobility scenarios with rapidly varying channels. Channel prediction, as an effective approach to acquire CSI, is considered a promising approach to improve the communication performance. However, most of the current prediction methods with the assumption of slowly varying channel components cannot cope with rapid variation. In this paper, we propose a novel channel prediction scheme to incorporate the mobility of both transceivers and scatterers. Based on the estimated mobility parameters, the component-wise channel extraction results are derived and then the channel frequency response is predicted. In addition, the prediction performance and the computational complexity of the proposed scheme are analyzed and evaluated, and the relationship between the mobility parameter estimation error and the channel component prediction accuracy is revealed as well. Through predicted results based on the simulated and measured data, the performance of the proposed scheme surpasses the conventional schemes with genie-aided information.