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A channel estimation approach for orthogonal frequency division multiplexing with multiple-input and multiple-output (MIMO-OFDM) in rapid fading channels is proposed. This approach combines the advantages of an optimal training sequence based least-square (OLS) algorithm and an expectation-maximization (EM) algorithm. The channels at the training blocks are estimated using an estimator based on the OLS algorithm. To compensate for the fast Rayleigh fading at the data blocks, a time domain based Gaussian interpolation filter is presented. Furthermore, an EM algorithm is introduced to improve the performance of channel estimation by a few iterations. Simulations show that this channel estimation approach can effectively track rapid channel variation.
A channel estimation approach for orthogonal frequency division multiplexing with multiple-input and multiple-output (MIMO-OFDM) in rapid fading channels is proposed. This approach combines an advantages of an optimal training sequence based least-square (OLS) algorithm and an expectation The maximalization (EM) algorithm. The channels at the training blocks are estimated using an estimator based on the OLS algorithm. To compensate for the fast Rayleigh fading at the data blocks, a time domain based Gaussian interpolation filter is presented. Furthermore, an EM algorithm is introduced to improve the performance of channel estimation by a few iterations. Simulations show that this channel estimation approach can effectively track rapid channel variation.