Temporal Correlation Based Sparse Channel Estimation For Tds-Ofdm In High-Speed Scenarios

Accurate channel estimation is essential for time domain synchronous OFDM (TDS-OFDM), which is a key enabling technology in digital terrestrial multimedia broadcasting (DTMB) standard. However, conventional channel estimation schemes for TDS-OFDM systems suffer from the obvious performance loss in high-speed scenarios. In this paper, by exploiting the temporal correlation of wireless channels, we propose a sparse channel estimation scheme to improve the channel estimation performance for TDS-OFDM systems in high-speed scenarios. Specifically, we first propose an overlap-add method of the received time-domain training sequences (TSs) to acquire the rough channel estimation, whereby the temporal correlation of wireless channels is exploited to improve the estimation performance of time-varying channels. Then, a priori information aided matching pursuit (PIA-MP) algorithm is proposed to acquire the accurate channel estimation with low complexity, whereby the priori information from the rough channel estimation is utilized to further improve the channel estimation accuracy. Simulation results demonstrate that the proposed scheme is superior to the state-of-the-art schemes in high-speed scenarios, especially under severe multipath channels with long delay spread.