Adaptive Channel Equalization for Wireless Personal Communications

In this paper, a new adaptive H1 filtering algorithm is developed to recursively update the tap-coefficient vector of a decision feedback equalizer (DFE) in order to adaptively equalize the time-variant dispersive fading channel of a high-rate indoor wireless personal communication system. Different from conventional L2 [such as the recursive least squares (RLS)] filtering algorithms which minimize the squared equalization error, the adaptive H1 filtering algorithm is a worst case optimization. It minimizes the effect of the worst disturbances (including input noise and modeling error) on the equalization error. Hence, the DFE with the adaptive H1 filtering algorithm is more robust to the disturbances than that with the RLS algorithm. Computer simulation demonstrates that better transmission performance can be achieved using the adaptive H1 algorithm when the received signal-to-noise ratio (SNR) is larger than 20 dB.