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In this paper, a novel pilot-aided algorithm is developed for multiple-input-multiple-output (MIMO) orthogonal frequency-division-multiplexing (OFDM) systems operating in a fast time-varying environment. The algorithm has been designed to work with both the parametric L -path channel model (with known path delays) and the equivalent discrete-time channel model to jointly estimate the multipath Rayleigh channel complex amplitude (CA) and the carrier frequency offset (CFO). Each CA time variation within one OFDM symbol is approximated by a basis expansion model representation. An autoregressive model is built for the parameters to be estimated. The algorithm performs estimation using extended Kalman filtering. The channel matrix is thus easily computed, and the data symbol is estimated without intercarrier interference (ICI) when the channel matrix is QR-decomposed. It is shown that our algorithm is far more robust to high speed than the conventional algorithm, and the performance approaches that of the ideal case for which the channel response and CFO are known.