Iterative channel estimation techniques for uplink MC-CDMA systems

In this work, maximum likelihood (ML) channel estimation for uplink multicarrier code-division multiple-access (MC-CDMA) systems is considered in the presence of frequency fading channel. The expectation-maximization (EM)- and a space-alternating generalized expectation-maximization (SAGE) algorithm are introduced to avoid matrix inversion for the ML channel estimation problem. We compare the both algorithms in terms of the number of used iteration and show that the proposed algorithms converge the same performance of the ML estimator as the increasing number of iterations.