Adaptive AR Channel Model Identification of Time-Varying Communication Systems

This paper implements an adaptive identification of autoregressive AR model coefficients for model-based filtering over time-varying communication channels. The presented approach does not require a-priori knowledge of the dynamics of the system which overcomes the issue of determining model coefficients that capture the dynamics of unknown time-varying channels. Simulation MSE performance analysis in a multiuser environment shows superior experimental performance of the AR(2) model-based adaptive algorithm with adaptive model identification, comparing to the AR(1) model-based adaptive algorithm with adaptive model identification, the same algorithm with fixed model coefficients and standard observation-only-based LMS and RLS adaptive algorithms.