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Experimental Characterization and Dynamic Modeling of THz Channels Under Fog Conditions

  • Jiabiao Zhao
  • , Kefeng Huang
  • , Xiaoxiang Li
  • , Mingxia Zhang
  • , Peian Li
  • , Wenbo Liu
  • , Jie Yang
  • , Yiming Zhao
  • , Weidong Hu
  • , Jianjun Ma*
  • *Corresponding author for this work
  • Beijing Institute of Technology
  • State Key Laboratory of Environment Characteristics and Effects for Near-Space

Research output: Contribution to journalArticlepeer-review

Abstract

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).

Original languageEnglish
JournalIEEE Transactions on Terahertz Science and Technology
DOIs
Publication statusAccepted/In press - 2026

Keywords

  • Terahertz channel
  • bit error rate
  • channel measurement and modeling
  • fog
  • fog droplet size distribution
  • power loss
  • power profile

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