This paper is concerned with the challenging problem of joint channel estimation and data detection for high mobility multiple-input multiple-output orthogonal frequency division multiplexing systems. We propose a new iterative channel estimation and detection scheme, which reduces the unexpected effects of both detection errors and channel estimation errors. Detection errors in channel estimation are analyzed and transformed as part of the noise. To filter this equivalent noise by Kalman estimator, we derive the covariance of both the channels and data errors in detection. Besides, we propose a new detection algorithm with an optimized weight to minimize the detection error caused by channel estimation errors. To obtain this optimized weight, the error covariance of the estimated channels is derived from the error estimate covariance matrix in Kalman estimator. Simulation results are presented to demonstrate the significant performance improvement in joint channel estimation and data detection with the proposed iterative scheme.
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