Subspace tracking of fast time-varying channels in precoded MIMO-OFDM systems

This paper presents a blind subspace-based tracking scheme for precoded MIMO-OFDM systems over rapidly time-varying wireless channels. Subspace-based tracking is normally considered for slow time-varying channels only. Thanks to the frequency correlation of the wireless channels, the proposed scheme is able to collect data not only from the time but also from the frequency domain to speed up the update of the required second-order statistics. After each update of the statistics, the subspace information is also updated using orthogonal iteration, and then a new channel estimate is computed. The proposed algorithm is verified in 3GPP-SCM suburban macro scenario, in which a mobile station is allowed to move in any direction with a constant speed of 100 km/h. The simulation results show that the root mean square error of the channel estimates converges to the level of 2 times 10^-2 within less than 5 OFDM symbols even for such a high Doppler rate.