Position-aided Large-scale MIMO Channel Estimation for High-Speed Railway Communication Systems

TL;DR

This paper introduces a position-aided channel estimation method for high-speed railway MIMO systems, maintaining high throughput despite increased mobility by leveraging antenna position information and joint spatial-temporal correlation.

Contribution

It proposes a novel position-aided channel estimation scheme that reduces training overhead and maintains throughput at high mobility levels, with analytical and simulation validation.

Findings

Throughput remains stable with increased mobility using the proposed scheme.

Optimal power, timing, and antenna size are identified for best performance.

The method outperforms conventional schemes in high-speed scenarios.

Abstract

We consider channel estimation for high-speed railway communication systems, where both the transmitter and the receiver are equipped with large-scale antenna arrays. It is known that the throughput of conventional training schemes monotonically decreases with the mobility. Assuming that the moving terminal employs a large linear antenna array, this paper proposes a position-aided channel estimation scheme whereby only a portion of the transmit antennas send pilot symbols and the full channel matrix can be well estimated by using these pilots together with the antenna position information based on the joint spatial-temporal correlation. The relationship between mobility and throughput/DoF is established. Furthermore, the optimal selections of transmit power and time interval partition between the training and data phases as well as the antenna size are presented accordingly. Both analytical and simulation results show that the system throughput with the position-aided channel estimator does not deteriorate appreciably as the mobility increases, which is sharply in contrast with the conventional one.