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An enhanced extended Kalman filtering (E2KF) algorithm is proposed in this paper to cope with the joint multiple carrier frequency offsets (CFOs) and time-variant channel estimate for MIMO-OFDM systems over high mobility scenarios. It is unveiled that, the auto-regressive (AR) model not only provides an effective method to capture the dynamics of the channel parameters, which enables the prediction capability in the EKF algorithm, but also suggests an method to incorporate multiple successive pilot symbols for the improved measurement update.

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