Airborne IMT users in precision agriculture: Monte-Carlo analysis of UAV interference in 694–2690 bands

The integration of unmanned aerial vehicles (UAVs) into precision agriculture, as envisioned in the agricultural systems, promises significant gains in crop monitoring, yield forecasting, and targeted agro-technical interventions. However, the use of IMT frequency bands for real-time UAV communications introduces new spectrum sharing and compatibility challenges. Unlike terrestrial user equipment, airborne agricultural drones operate always outdoors, above the base-station downtilt, with predominantly line-of-sight (LoS) propagation to multiple cells, drastically altering compatibility conditions and potentially increasing interference to other operators. This paper proposes a Monte Carlo-based simulation framework analysis of interference generated by such UAVs in IMT frequency allocations across 694–2690 MHz. Simulations model rural and urban macrocell deployments typical of large-scale farmlands, incorporating 3D antenna patterns, altitude-dependent air-to-ground channel models, realistic LTE/NR power-control schemes, and UAV operational patterns. Key metrics include aggregate uplink interference at victim cells, downlink degradation at UAVs, and cross-link interference in TDD systems. Results show that even low-power UAV transmissions can exceed harmful interference thresholds in multiple adjacent-channel cells. Operational recommendations are provided to ensure coexistence of precision-agriculture UAVs with terrestrial IMT networks.

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Publication Details

Journal
Frontiers in Signal Processing
Published
2026-03-05
DOI
https://doi.org/10.3389/frsip.2026.1764383
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
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article

Airborne IMT users in precision agriculture: Monte-Carlo analysis of UAV interference in 694–2690 bands

Karina Turzhanova, Alexander Pastukh, Valery Tikhvinskiy, Yelizaveta Vitulyova et al.
Frontiers in Signal Processing
UAV Applications and Optimization
article

Airborne IMT users in precision agriculture: Monte-Carlo analysis of UAV interference in 694–2690 bands

Karina Turzhanova, Alexander Pastukh, Valery Tikhvinskiy, Yelizaveta Vitulyova, Alexandr Solochshenko
article en

Abstract

The integration of unmanned aerial vehicles (UAVs) into precision agriculture, as envisioned in the agricultural systems, promises significant gains in crop monitoring, yield forecasting, and targeted agro-technical interventions. However, the use of IMT frequency bands for real-time UAV communications introduces new spectrum sharing and compatibility challenges. Unlike terrestrial user equipment, airborne agricultural drones operate always outdoors, above the base-station downtilt, with predominantly line-of-sight (LoS) propagation to multiple cells, drastically altering compatibility conditions and potentially increasing interference to other operators. This paper proposes a Monte Carlo-based simulation framework analysis of interference generated by such UAVs in IMT frequency allocations across 694–2690 MHz. Simulations model rural and urban macrocell deployments typical of large-scale farmlands, incorporating 3D antenna patterns, altitude-dependent air-to-ground channel models, realistic LTE/NR power-control schemes, and UAV operational patterns. Key metrics include aggregate uplink interference at victim cells, downlink degradation at UAVs, and cross-link interference in TDD systems. Results show that even low-power UAV transmissions can exceed harmful interference thresholds in multiple adjacent-channel cells. Operational recommendations are provided to ensure coexistence of precision-agriculture UAVs with terrestrial IMT networks.

Frontiers in Signal ProcessingVol. 6
National Research University Higher School of Economics (RU), Satbayev University (KZ), Almaty University of Power Engineering and Telecommunications (KZ), Digital Science (United States) (US), Pakistan Telecommunication Company (Pakistan) (PK), International Technological University (US)
Zero hunger
Openalex Percentile: Top 35%
UAV Applications and Optimization
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