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

In this paper, an LMS decision feedback equalizer (DFE) with Kalman algorithm used in training period is proposed for terrestrial HDTV broadcasting. The utilization of Kalman algorithm is intended solely for fast startup and optimality of estimating the equalization coefficients. The LMS algorithm is employed in decision-directed mode primarily due to its simplicity, robustness and good tracking behaviors. The Kalman algorithm is implemented in a non-realtime 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 x 10(-6) with respect to the conventional LMS DFE scheme suggested by Grand Alliance.