Hybrid Kalman/LMS decision feedback equalization strategy for terrestrial HDTV channels

Abstract

An LMS decision feedback equalizer (DFE) with the Kalman algorithm used in training period is proposed for terrestrial HDTV broadcasting. The utilization of Kalman's algorithm is intended solely for fast startup and optimality of estimating the equalization coefficients. The LMS algorithm is employed in a decision-directed mode primarily due to its simplicity, robustness and good tracking behavior. The Kalman algorithm is implemented in a non-real-time manner (i.e. off-line), rather than real-time, to drastically reduce computational requirement for practical realization. The only penalty paid is an acceptable or tolerable small time delay. Simulation results show that this equalization strategy provides almost 3.0 dB signal-to-noise ratio (SNR) improvement at a BER of 3.0/spl times/10/sup -6/ with respect to the conventional LMS DFE scheme suggested by the Grand Alliance.