A SAGE-Based Joint Parameter Estimation of OFDM System

In this paper, by using an approximate application of the space-alternating generalized expectation-maximization (SAGE) algorithm, we propose an iterative residual frequency offset (RFO) tracking and channel state information (CSI) estimation as well as data detection scheme for orthogonal frequency division multiplexing (OFDM) systems. In the proposed scheme, two processes are considered. The expectation step divided the received signals into multiple hidden signals in time domain. The hidden signals, as "complete data", will be used to calculate the expectation of the likelihood function. In the maximum step, by maximize the expectation of likelihood function, the required parameters - RFO, CSI and data symbols - are estimated sequentially in an approximate method by expanding second-order Taylor series. Simulation results confirm the performance and effectiveness of the proposed algorithm.