Key technologies for wireless network digital twin towards smart railways

Abstract

An emerging railway technology called smart railway promises to deliver higher transportation efficiency, enhanced comfort in services, and greater eco-friendliness. The smart railway is expected to integrate fifth-generation mobile communication (5G), Artificial Intelligence (AI), and other technologies, which poses new problems in the construction, operation and maintenance of railway wireless networks. Wireless Digital Twins (DTs), which have recently emerged as a new paradigm for the design of wireless networks, can address these problems and enable the whole lifecycle management of railway wireless networks. However, there are still many scientific issues and challenges for railway-oriented wireless DT. Relevant key technologies to solve these problems are introduced and described, including characterization of materials' physical-EM properties, autonomous reconstruction of Three-dimensional (3D) environment model, AI-empowered environmental cognition, Ray-Tracing (RT), model-based and AI-based RT acceleration, and generation of multi-spectra sensing data. Moreover, this paper presents our research results for each key technology and describes the wireless network planning and optimization system based on high-performance RT developed by our laboratory. This paper outlines the framework for realizing the wireless DT of smart railways, providing the direction for future research.

Keywords

Digital twin / Smart railways / Ray tracing / Channel characterization

Decalaration of Competing Interest

The authors declare that they have no competing interests.

Acknowledgement

This work was supported by Beijing Natural Science Foundation (L212029, L221009), the National Natural Science Foundation of China (62271043, 62371033), and the Ministry of Education of China (8091B032123).

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