A Three-Dimensional Path Loss Model for THz Band Aerial Communications
arXiv:2603.29385v1 Announce Type: new Abstract: Accurate characterization of Terahertz (THz) band path loss is critical for reliable high-frequency communication, especially in aerial networks where transceivers may operate at different altitudes. Existing THz-band path loss models for aerial networks focus on horizontal or vertical transceiver deployments, and fall short at modeling the random 3D geometry of transceiver locations. To address this limitation, we propose a new analytical THz path loss model that incorporates arbitrary 3D geometry of transceiver locations and frequency-selective absorption, obtained through a two-dimensional regression. We validate our proposed model with the propagation data collected via the Atmospheric Model (am) tool for multiple aerial link types, inclu
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Abstract:Accurate characterization of Terahertz (THz) band path loss is critical for reliable high-frequency communication, especially in aerial networks where transceivers may operate at different altitudes. Existing THz-band path loss models for aerial networks focus on horizontal or vertical transceiver deployments, and fall short at modeling the random 3D geometry of transceiver locations. To address this limitation, we propose a new analytical THz path loss model that incorporates arbitrary 3D geometry of transceiver locations and frequency-selective absorption, obtained through a two-dimensional regression. We validate our proposed model with the propagation data collected via the Atmospheric Model (am) tool for multiple aerial link types, including drone-to-drone (Dr2Dr), medium-altitude aerial communication (MAAC), high-altitude unmanned aerial vehicles~(UAV)-to-UAV (U2U) links over varying transceiver separation and sub-THz to low-THz spectrum, i.e., 0.1--1~THz. The proposed framework provides a unified and accurate model for analyzing and designing future high-frequency aerial communication systems.
Comments: This paper has been accepted for presentation at the IEEE International Conference on Communications (ICC), 2026, and will appear in the conference proceedings
Subjects:
Signal Processing (eess.SP)
Cite as: arXiv:2603.29385 [eess.SP]
(or arXiv:2603.29385v1 [eess.SP] for this version)
https://doi.org/10.48550/arXiv.2603.29385
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Caglar Tunc [view email] [v1] Tue, 31 Mar 2026 07:54:26 UTC (613 KB)
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