Digital Twin Empowered In-Vehicular Channel Modeling and Wireless Planning in the Terahertz Band
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arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866918196002422784 |
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| author | Zhu, Mingjie Lyu, Yejian Han, Chong |
| author_facet | Zhu, Mingjie Lyu, Yejian Han, Chong |
| contents | Vehicle-to-everything (V2X) technology has emerged as a key enabler of intelligent transportation systems, while the Terahertz (THz) band offers abundant spectrum resources to support ultra-high-speed and low-latency V2X communications. This paper investigates the in-vehicle wireless channel in the 300~GHz band. First, channel measurement based on vector-network-analyzer (VNA) is conducted under typical V2X scenarios, including with/without human, and window-on/off cases. Then, a digital twin (DT) of the vehicle is constructed from high-resolution point cloud data and a measurement-based material property database. The DT is integrated into an open-source ray-tracing (RT) simulator, Sionna, to model multipath propagation. The DT-empowered simulation results are analyzed and validated with the measurement data, showing strong agreement and validating the feasibility. Finally, a hybrid ray-tracing-statistic channel model is established, combining the RT results and measurement data. Leveraging the validated model, further wireless planning is carried out, including signal-to-interference-plus-noise ratio (SINR) analysis, coverage probability evaluation, and optimal transmitter (Tx) placement. These findings provide valuable insights for the design and deployment of future THz in-vehicle communication systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_07789 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Digital Twin Empowered In-Vehicular Channel Modeling and Wireless Planning in the Terahertz Band Zhu, Mingjie Lyu, Yejian Han, Chong Information Theory Vehicle-to-everything (V2X) technology has emerged as a key enabler of intelligent transportation systems, while the Terahertz (THz) band offers abundant spectrum resources to support ultra-high-speed and low-latency V2X communications. This paper investigates the in-vehicle wireless channel in the 300~GHz band. First, channel measurement based on vector-network-analyzer (VNA) is conducted under typical V2X scenarios, including with/without human, and window-on/off cases. Then, a digital twin (DT) of the vehicle is constructed from high-resolution point cloud data and a measurement-based material property database. The DT is integrated into an open-source ray-tracing (RT) simulator, Sionna, to model multipath propagation. The DT-empowered simulation results are analyzed and validated with the measurement data, showing strong agreement and validating the feasibility. Finally, a hybrid ray-tracing-statistic channel model is established, combining the RT results and measurement data. Leveraging the validated model, further wireless planning is carried out, including signal-to-interference-plus-noise ratio (SINR) analysis, coverage probability evaluation, and optimal transmitter (Tx) placement. These findings provide valuable insights for the design and deployment of future THz in-vehicle communication systems. |
| title | Digital Twin Empowered In-Vehicular Channel Modeling and Wireless Planning in the Terahertz Band |
| topic | Information Theory |
| url | https://arxiv.org/abs/2511.07789 |