Experimental Characterization and Dynamic Modeling of THz Channels Under Fog Conditions
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arXiv
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| Main Authors: | , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866914087552679936 |
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| author | Zhao, Jiaobiao Huang, Kefeng Li, Xiaoxiang Zhang, Mingxia Li, Peian Yang, Jie Liu, Wenbo Zhao, Yiming Hu, Weidong Ma, Jianjun |
| author_facet | Zhao, Jiaobiao Huang, Kefeng Li, Xiaoxiang Zhang, Mingxia Li, Peian Yang, Jie Liu, Wenbo Zhao, Yiming Hu, Weidong Ma, Jianjun |
| contents | The terahertz (THz) band is a promising candidate for sixth-generation wireless networks, but its deploymen in outdoor environments is challenged by meteorological phenomena, particularly fog, which imposes variable and difficult-to-predict channel degradation. This article introduces dynamic channel model for the THz band explicitly driven by the time-evolving droplet size distribution (DSD) of fog, integrating real-time microphysical sensing to capture variations in the fog microstructure. Experimental measurements were conducted at 220 GHz and 320 GHz in a controlled fog chamber to achieve quasi-stationary states, and a larger room-scale setup to characterize dynamic, non-stationary fog evolution. The results confirm that channel power loss is overwhelmingly dominated by absorption rather than scattering, validating the use of the computationally efficient Rayleigh approximation below 1 THz. Statistical analysis revealed exceptionally high Rician K-factors, demonstrating that THz channels maintain strong line-of-sight stability even in dense fog. System-level performance analysis shows that degradation in bit error rate is driven by the slow, gradual evolution of the DSD, rather than fast multipath fading. This finding enables the reliable simplification of the THz fog channel into a near-Gaussian channel model with time-varying signal-to-noise ratio. This microphysics-aware approach established here provides the necessary foundation for developing adaptive system designs centered on SNR tracking for robust future THz networks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_09906 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Experimental Characterization and Dynamic Modeling of THz Channels Under Fog Conditions Zhao, Jiaobiao Huang, Kefeng Li, Xiaoxiang Zhang, Mingxia Li, Peian Yang, Jie Liu, Wenbo Zhao, Yiming Hu, Weidong Ma, Jianjun Applied Physics The terahertz (THz) band is a promising candidate for sixth-generation wireless networks, but its deploymen in outdoor environments is challenged by meteorological phenomena, particularly fog, which imposes variable and difficult-to-predict channel degradation. This article introduces dynamic channel model for the THz band explicitly driven by the time-evolving droplet size distribution (DSD) of fog, integrating real-time microphysical sensing to capture variations in the fog microstructure. Experimental measurements were conducted at 220 GHz and 320 GHz in a controlled fog chamber to achieve quasi-stationary states, and a larger room-scale setup to characterize dynamic, non-stationary fog evolution. The results confirm that channel power loss is overwhelmingly dominated by absorption rather than scattering, validating the use of the computationally efficient Rayleigh approximation below 1 THz. Statistical analysis revealed exceptionally high Rician K-factors, demonstrating that THz channels maintain strong line-of-sight stability even in dense fog. System-level performance analysis shows that degradation in bit error rate is driven by the slow, gradual evolution of the DSD, rather than fast multipath fading. This finding enables the reliable simplification of the THz fog channel into a near-Gaussian channel model with time-varying signal-to-noise ratio. This microphysics-aware approach established here provides the necessary foundation for developing adaptive system designs centered on SNR tracking for robust future THz networks. |
| title | Experimental Characterization and Dynamic Modeling of THz Channels Under Fog Conditions |
| topic | Applied Physics |
| url | https://arxiv.org/abs/2510.09906 |