Adaptive equalization based on internal model principle for time-varying fading channels

A novel adaptive filtering algorithm is presented to identify the time-varying parameters of an FIR channel model. The proposed weights adjusting algorithm incorporates an internal model for compensating the dynamics of the time-varying model parameters. The stability of the adaptive filter can be assured by designing the weights adjusting dynamics in the adaptive algorithm by applying the passivity theorem and the small gain theorem. Its effectiveness of the proposed LMS and RLS types of algorithms is validated by comparing to ordinary LMS approaches in numerical simulation of adaptive identification and decision-feedback equalization of a time-varying fading channel with parameters changing with a first-order function of time.