The polynomial-based generalized recursive least squares estimator for Rayleigh fading channels

This paper presents a polynomial-based generalized recursive least squares channel estimator for the dispersive Rayleigh fading channel. The estimator is formulated using a state transition matrix based on polynomial prediction instead of autoregressive modelling, and does not require channel statistics to operate. Analytical and simulated mean square deviation results for the tracking performance of the estimator are presented. The results show that by selecting appropriate values of the "forget factor" and polynomial order, the estimator performs almost as well as the optimal Kalman estimator even in fast fading.