Enabling Network Technologies For Flexible Railway Connectivity

Abstract

Today’s rail industry deploys innovative applications for real-time monitoring of trains and railway infrastructures and remote control of trains to enhance the safety and security of passengers and train operation. These applications can require multiple constraints satisfactions in terms of latency, data rate, reliability, coverage, mobility, security, etc. In order to meet the desired quality of users’ (trains, passengers, controllers, etc.,) experience, it is essential to apply and combine various enabling wireless technologies for the railway communications architecture such as end-to-end (from the cloud hosting applications to the user client, traversing communication network infrastructure) Network Slicing (NS), Software Defined Network (SDN), Network Function Virtualization (NFV), Multi-access Edge Computing (MEC), Blockchain, Artificial Intelligence (AI) tools, etc. This paper aims to propose a global unified control framework to automatically compute deploy, and manage necessary resources on the different network infrastructures (cloud, core, transport, and multiple-access networks). In this context, this article proposes the first study in the railway sector to link application constraints and enabling technologies. After a brief overview of the railway context, the main applications requirements, and the technologies that could be applied, we propose a high-level architecture for railway applications incorporating the various technologies identified: MEC, NFV, SDN, AI tools, and Blockchain. We also study the impact that these different technologies could have on existing rail applications and identify the challenges and future directions for rail networks in the era of 5G and future 6G.

Keywords

• Railway
• 5G
• network slicing
• quality of service (QoS)
• AI
• edge computing