Estimation and identification of time-varying long-term fading wireless channels with application to power control

This paper is concerned with modeling of time-varying wireless fading channels, parameter estimation, identification, and optimal power control from received signal measurements. Wireless channels are represented by stochastic differential equations, which parameters and state variables are estimated using Expectation Maximization and Kalman filtering, respectively. The latter are carried out solely from received signal measurements. These algorithms estimate the channel path-loss and identify the channel parameters recursively. An optimal power control algorithm based on the estimated parameters and channel states is proposed. Numerical results are presented to test the efficiency of the proposed channel estimation and identification algorithms, and to indicate that a significant gain in performance can be achieved using the proposed approach.