Positioning of High-Speed Trains Using 5G Networks

This paper is focused on the study of a high-speed train (HST) positioning system using 5G millimeter wave (mmwave) technology. Using MATLAB and its 5G toolbox, a 5G network architecture for high-speed railway lines was deployed by following the 3GPPrecommended layout, on top of which a positioning service was implemented by using 5G Positioning Reference Signals (PRS) and positioning estimation methods based on Time of Arrival (TOA) and Time Difference of Arrival (TDOA) techniques. In addition, to improve the accuracy, a novel positioning algorithm with a hybrid TOA and TDOA method was introduced and tested. The results of the simulation show an accuracy below 10 meters, available for 80% of time with a train speed of up to $350 \mathrm{~km} / \mathrm{h}$ for all three implemented methods, which is in alignment with the requirements specified by 3GPP for commercial use cases. Furthermore, with our TOA+TDOA hybrid method, a residual error below 5 meters was obtained for 95% of the time with a train speed of up to 350 $\mathrm{km} / \mathrm{h}$, which is sufficient for some of the non-safety-relevant applications in a HST scenario.