Tracking Time-Varying Channel in Impulse Noise Environment Based on Kalman Filter

Abstract

A new algorithm for tracking time-varying fading channels in impulse noise environment is proposed in this paper, which uses the Kalman filter based on Clarke's model. However, the Kalman filter is known to be sensitive to impulse noise. In this paper, we investigate into how to restrain the adverse effect of impulse noise. The impulsive noise is modeled as a two-term Gaussian mixture distribution. The proposed channel tracking scheme is based on a state-space representation of the communication system and the prior information of the measurement noise. To reduce the complexity of the high-dimensional Kalman filter for channel estimation of the paths, we use a low-dimensional Kalman filter for the estimation of each path. Simulations show this algorithm is much less sensitive to impulse noise than the conventional algorithms, and is effective for the estimation of the fading channel when the performance of the channel estimation is presented in terms of the mean-square error (MSE).