3-D Mobile-to-Mobile channel tracking with first-order autoregressive model-based Kalman filter

This paper deals with channel estimation in Mobile-to-Mobile communication assuming three-dimensional scattering environment. It approximates the channel by a first-order autoregressive (AR(1)) model and tracks it by a Kalman filter. The common method used in the literature to estimate the parameter of AR(1) model is based on a correlation matching criterion. We propose another criterion based on the Minimization of the Asymptotic Variance of the Kalman filter, and we justify why it is more appropriate for slow fading variations. This paper provides the closed-form expression of the optimal AR(1) parameter under minimum asymptotic variance criterion and the approximated expression of the estimation variance in output of the Kalman filter, both for Fixed-to-Mobile and Mobile-to-Mobile communication channels.