Autoregressive Channel Prediction Model for Cognitive Radio

An autoregressive channel prediction model is presented for cognitive radio systems. This model adopts a second-order AR model and a particle filter. In this paper, an AR model of order p is used to approximate the flat Rayleigh fading channels. Simulation results show that the performance of the proposed autoregressive channel prediction model based on particle filtering is better than that of Kalman filtering.