Advanced 6 G wireless communication technologies for intelligent high-speed railways

Abstract

The rapid expansion of railways, especially High-Speed Railways (HSRs), has drawn considerable interest from both academic and industrial sectors. To meet the future vision of smart rail communications, the rail transport industry must innovate in key technologies to ensure high-quality transmissions for passengers and railway operations. These systems must function effectively under high mobility conditions while prioritizing safety, eco-friendliness, comfort, transparency, predictability, and reliability. On the other hand, the proposal of 6 G wireless technology introduces new possibilities for innovation in communication technologies, which may truly realize the current vision of HSR. Therefore, this article gives a review of the current advanced 6 G wireless communication technologies for HSR, including random access and switching, channel estimation and beamforming, integrated sensing and communication, and edge computing. The main application scenarios of these technologies are reviewed, as well as their current research status and challenges, followed by an outlook on future development directions.

Keywords

High-speed railway / Random access and switching / Channel estimation and beamforming / Integrated sensing and communication / Edge computing

CRediT authorship contribution statement

Wei Chen: Writing – original draft. Cong Yu: Writing – original draft. Yuxuan Sun: Writing – original draft, Supervision. Bo Ai: Writing – review & editing. Bowen Zhang: Writing – review & editing. Chau Yuen: Writing – review & editing.

Declaration of Competing Interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Yuxuan Sun and Bo Ai report financial support was provided by Beijing Jiaotong University. Chau Yuen reports financial support was provided by Nanyang Technological University. Bowen Zhang reports financial support was provided by Imperial College London. Wei Chen reports financial support was provided by Beijing Jiaotong University. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This work is supported by National Natural Science Foundation of China (U2468201, 62122012, 62221001).

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