TWO APPROACHES ON CARRIER FREQUENCY OFFSET ESTIMATION IN MIMO OFDM SYSTEMS

We consider the problem of joint carrier frequency offset and channel estimationbetween transmitter and receiver in a frequency-selective channel MIMO-OFDM system. Recentlytwo high performance estimators based on the expectation-maximization (EM) algorithm havebeen proposed. The main drawback of the maximum likelihood base algorithms, like EMalgorithm, is the high computational complexity. In this paper, we propose an extended Kalmanfilter based estimator, which has higher performance than that of EM algorithm, while itscomputational complexity is lower. In addition, the Particle Swarm Optimization (PSO) algorithmis used for joint ML estimation of carrier frequency offset and channel parameters for the generalmodel. The proposed method has a lower computational complexity than that of traditional searchmethods. Simulation results in comparison with Cramer-Rao bound show that the proposedalgorithms outperform the EM in all ranges of signal-to-noise ratio for both channel and frequencyoffset estimations. Also, among them, the PSO algorithm is superior.