Adaptive H∞ channel equalization for wireless personal communications

In this paper, a new adaptive H-infinity 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 L-2 [such as the recursive least squares (RLS)] filtering algorithms which minimize the squared equalization error, the adaptive H-infinity 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 H-infinity 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 H-infinity algorithm when the received signal-to-noise ratio (SNR) is larger than 20 dB.