Analysis of Joint Channel Estimation and Equalization using a Kalman Filter

Multipath fading is a major impediment to reliable high data rate communications over wireless channels. It has been demonstrated that Kalman filters can be used for joint channel estimation and symbol detection to counteract the negative effects of the multipath radio channel on wireless receiver performance. Improvements are possible if Kalman filters based on higher order auto-regressive (AR) models of the radio channels are used but the calculation of the AR model values is ill-conditioned. Recently, a method was introduced for calculating the parameters using an over-determined linear system. This paper introduces the use of these methods for Kalman filters applied for joint channel estimation and symbol detection. These filters reduce the error rate compared to previous filters with only a slightly higher computational cost. The resulting Kalman filters are also robust to variations in the mobility model and noise powers