SAGE algorithm based channel estimation for uplink STBC-MC-CDMA systems

In this work, maximum likelihood (ML) channel estimation for uplink space time block coded multicarrier code-division multiple-access (STBC-MC-CDMA) systems is considered in the presence of frequency selective channel. It is shown that the ML channel estimation requires matrix inversion and its calculation requires significant computation for increasing of total active users and the length of channel. Therefore, the space-alternating generalized expectation-maximization (SAGE) algorithm is introduced to achieve the same performance with the ML channel estimation. We compared SAGE algorithm 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 while it requires significantly lower computational complexity.