Compressed Channel Estimation With Position-Based ICI Elimination for High-Mobility SIMO-OFDM Systems

Abstract

Orthogonal frequency-division multiplexing (OFDM) is widely adopted for providing reliable and high-data-rate communication in high-speed train (HST) systems. However, with increasing train mobility, the resulting large Doppler shift introduces intercarrier interference (ICI) in OFDM systems and greatly degrades channel estimation accuracy. Therefore, it is necessary and important to investigate reliable channel estimation and ICI mitigation methods in high-mobility environments. In this paper, we consider a typical HST communication system and show that the ICI caused by large Doppler shifts can be mitigated by exploiting the train position information and the sparsity of the basis expansion model (BEM)-based channel model. Then, we show that for the complex-exponential BEM (CE-BEM)-based channel model, the ICI can be completely eliminated to get the ICI-free pilots at each receive antenna. After that, we propose a new pilot pattern design algorithm to reduce system coherence to improve the compressed-sensing-based channel estimation accuracy. The proposed optimal pilot pattern is independent of the number of receive antennas, the Doppler shifts, train position, or train speed. Simulation results confirm the effectiveness of the proposed scheme in high-mobility environments. The results also show that the proposed scheme is robust to the speed of the moving train.