{"ID":2851628,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.19401","arxiv_id":"2510.19401","title":"Ray-Tracing Based Narrow-Beam Channel Simulation, Characterization and Performance Evaluation for 5G-R Systems","abstract":"This paper investigates narrow-beam channel characterization and performance evaluation for 5G for railway (5G-R) systems based on ray-tracing (RT) simulation. Three representative high-speed railway (HSR) scenarios including viaduct, cutting, and station are established, and RT-based dynamic narrow-beam channel simulations are conducted using a designed beam tracking scheme that ensures continuous alignment with the moving train. The channel characteristics are analyzed in terms of both large-scale and small-scale fading, as well as non-stationarity, providing statistical insights into path loss, shadow fading, fading severity, time-frequency-space dispersion, and stationarity interval. The influence of beamwidth on these channel properties is also examined. Furthermore, the performance of 5G-R systems operating in such narrow-beam channels is evaluated using the Vienna 5G simulator, with a focus on block error rate, throughput, and spectral efficiency. A hardware-in-the-loop simulation platform is developed to further assess synchronization signal reference signal received power, signal-to-interference-plus-noise ratio, and reference signal received quality. The results provide valuable guidance for the design and optimization of 5G-R systems in HSR environments.","short_abstract":"This paper investigates narrow-beam channel characterization and performance evaluation for 5G for railway (5G-R) systems based on ray-tracing (RT) simulation. Three representative high-speed railway (HSR) scenarios including viaduct, cutting, and station are established, and RT-based dynamic narrow-beam channel simula...","url_abs":"https://arxiv.org/abs/2510.19401","url_pdf":"https://arxiv.org/pdf/2510.19401v2","authors":"[\"Tao Zhou\",\"Liying Geng\",\"Kaifeng Bao\",\"Tianyun Feng\",\"Liu Liu\",\"Bo Ai\"]","published":"2025-10-22T09:21:31Z","proceeding":"eess.SP","tasks":"[\"eess.SP\"]","methods":"[]","has_code":false}