TY - JOUR
T1 - Experimental Characterization and Dynamic Modeling of THz Channels Under Fog Conditions
AU - Zhao, Jiabiao
AU - Huang, Kefeng
AU - Li, Xiaoxiang
AU - Zhang, Mingxia
AU - Li, Peian
AU - Liu, Wenbo
AU - Yang, Jie
AU - Zhao, Yiming
AU - Hu, Weidong
AU - Ma, Jianjun
N1 - Publisher Copyright:
© 2011-2012 IEEE.
PY - 2026
Y1 - 2026
N2 - The terahertz (THz) band is a promising candidate for sixth-generation wireless networks, but its deployment in outdoor environments is challenged by meteorological phenomena, particularly fog, which imposes variable and difficult-to-predict channel degradation. This article introduces a 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. The model is validated for quasi stationary fog conditions, subject to the operating limits of the microphysical sensor. 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 lower computational complexity 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 (SNR).
AB - The terahertz (THz) band is a promising candidate for sixth-generation wireless networks, but its deployment in outdoor environments is challenged by meteorological phenomena, particularly fog, which imposes variable and difficult-to-predict channel degradation. This article introduces a 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. The model is validated for quasi stationary fog conditions, subject to the operating limits of the microphysical sensor. 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 lower computational complexity 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 (SNR).
KW - Terahertz channel
KW - bit error rate
KW - channel measurement and modeling
KW - fog
KW - fog droplet size distribution
KW - power loss
KW - power profile
UR - https://www.scopus.com/pages/publications/105038927483
U2 - 10.1109/TTHZ.2026.3693840
DO - 10.1109/TTHZ.2026.3693840
M3 - Article
AN - SCOPUS:105038927483
SN - 2156-342X
JO - IEEE Transactions on Terahertz Science and Technology
JF - IEEE Transactions on Terahertz Science and Technology
ER -