The problem of linear tracking of fast Rayleigh-faded MIMO channels is considered. Due to computational complexity limitations, Kalman filters based on low-order autoregressive (AR) models are often used although realistic Rayleigh-faded channels cannot be properly approximated by low-order AR models. By increasing the order of the AR model, the channel tracking performance is considerably improved, but the resulting computational complexity may become large. In this paper, the filters used to track the channel are restricted to have a recursive structure, based on the previous estimate and new observation. The knowledge of the autocorrelation function of the channel taps is used to derive filters that are significantly less complex than high-order AR model based Kalman filters at the price of only a minor degradation in performance.
['Yoav Levinbook', 'Tan F. Wong']
Linear Recursive Tracking of Fast Rayleigh-Faded MIMO Channels