Robust High-Speed Train Handover Optimization Using Velocity-Adaptive Fuzzy Logic in 5G/B5G Networks
Résumé
Efficient communication in High-Speed Trains (HSTs) is a crucial factor in maintaining reliable, safe, and continuous railway operations. However, high speed affects the handover process to a large extent, leading to interrupted communication services due to the rapid crossing of adjacent cells and variations in the radio channel. This problem is more pronounced in fifth-generation (5G) and Beyond 5G (B5G) networks, where the dense deployment of cells increases the Handover Rates (HORs). Traditional Event A3-based algorithms rely on fixed Handover Control Parameters (HCPs) that are unable to adapt to rapidly deteriorating link quality and increasingly unstable wireless channels as the train speed increases. Therefore, in this study, we propose a Velocity-Adaptive Dual-Segment Fuzzy Logic Controller (VADFLC) that can adjust the HCPs based on the Reference Signal Received Power (RSRP) and speed of the User Equipment (UE). The approach is implemented in a MATLAB simulation tool and validated against the Traditional A3 algorithm. The results show that the proposed method reduces the HOR by approximately 25.5% compared to the Traditional A3 algorithm, significantly lowers the Handover Ping-Pong (HOPP) ratio by up to 95%, and improves Handover Delay (HOD) behavior, with the delay decreasing by approximately 33% as the UE speed increases. In addition, an average delay reduction of approximately 1.0% is achieved under a different 5G for Railways (5G-R) simulation setup.
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