Kalman filter channel tracking algorithm based on AR model in WCDMA systems

In the standard of third generation digital mobile communications, there are pilot symbols in each slot, namely the training sequence. The traditional methods estimate the pilot channel using pilot information, estimate the data channel by interpolation or decision-feedback, and then obtain the transmitted information by channel equalization. Using a Kalman filter is a commonly used method for tracking channel variations. In this paper, we propose an algorithm which uses the Kalman filter based on the AR model to track a time-varying channel. We investigate how to estimate the channel and implement an equalizer by the Kalman filter in a DS-CDMA system. We apply two methods to obtain the AR coefficients, one is the adaptive LMS algorithm, and the other is Durbin's recursion method. Simulations show the algorithm is effective for the estimation of the frequence-selective fading channel.