In this paper, we present a joint time-variant carrier frequency offset (CFO) and frequency-selective channel response estimation scheme for multiple input-multiple output-orthogonal frequency-division multiplexing (MIMO-OFDM) systems for mobile users. The signal model of the MIMO-OFDM system is introduced, and the joint estimator is derived according to the maximum likelihood criterion. The proposed algorithm can be separated into three major parts. In the first part of the proposed algorithm, an initial CFO is estimated using derotation, and the result is used to apply a frequency-domain equalizer. In the second part, an iterative method is employed to locate the fine frequency peak for better CFO estimation. An adaptive process is used in the third part of the proposed algorithm to obtain the updated CFO estimation and track parameter time variations, including the time-varying CFOs and time-varying channels. The computational complexity of the proposed algorithm is considerably lower than that of the maximum likelihood-based grid search method. In a simulation, the mean squared error performance of the proposed algorithm was close to the Cramer-Rao lower bound. The simulation results indicate that the proposed novel joint estimation algorithm provides a bit error rate performance close to that in the perfect channel estimation condition. The results also suggest that the proposed method has reliable tracking performance in Jakes’ channel models.

Subspace-based blind carrier frequency offset (CFO) estimation algorithms in orthogonal frequency division multiple access (OFDMA) systems have been developed in the literature. However, the algorithms have some restrictions or require high computational complexity. In this paper, we propose simple iteration schemes to reduce complexity with an adaptive manner and present a time-variant CFO adaptive estimation method. In the first part of the proposed algorithm, with initial rough estimated CFOs, it employs iterative methods to obtain CFO estimates. And the second part is to use proposed adaptive process to obtain the updated CFO estimation and track the parameters' time-variations. The simulation results demonstrate the efficacy of the proposed iteration and adaptive schemes and the mean squared errors are near to the Cramer-Rao bounds.

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