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Updated: Sep 18, 2025

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Energy-Efficient Deployment Simulator of UAV-Mounted Base Stations Under Dynamic Weather Conditions.

Gyeonghyeon Min1, Jaewoo So1

  • 1Department of Electronic Engineering, Sogang University, Seoul 04107, Republic of Korea.

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|June 27, 2025
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Summary
This summary is machine-generated.

This study introduces an energy-efficient deployment strategy for unmanned aerial vehicle (UAV)-mounted base stations (MBSs) using a hybrid optimization algorithm. The method enhances network performance by optimizing UAV position and power, considering weather and terrain for improved quality of service.

Keywords:
UAV-MBS deploymentenergy efficiencygeolocation-aware simulatorhybrid ISA-PSOweather attenuation

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Area of Science:

  • Wireless Communications
  • Network Engineering
  • Optimization Algorithms

Background:

  • User equipment (UE) in unmanned aerial vehicle (UAV)-mounted base station (MBS) networks face dynamic channel variations due to UAV mobility and weather.
  • Degradation in quality of service (QoS) necessitates optimized deployment of UAV-MBS, considering 3D position, transmission power, and environmental factors.

Purpose of the Study:

  • To propose an energy-efficient UAV-MBS deployment scheme for multi-UAV-MBS networks.
  • To optimize the three-dimensional (3D) position and transmission power of each UAV-MBS.
  • To develop a practical deployment simulator incorporating geographical and meteorological data.

Main Methods:

  • A hybrid improved simulated annealing-particle swarm optimization (ISA-PSO) algorithm was employed to determine UAV-MBS 3D positions and transmission power.
  • A simulator was developed to model UAV-MBS deployment, integrating dynamic weather conditions, terrain data, and geolocation.
  • Performance was evaluated against conventional deployment approaches.

Main Results:

  • The proposed ISA-PSO based deployment scheme demonstrated faster convergence compared to traditional methods.
  • The scheme achieved higher stability in optimizing UAV-MBS parameters.
  • The developed simulator provided more practical deployment results by considering real-time weather and terrain.

Conclusions:

  • The proposed energy-efficient deployment scheme offers superior performance for UAV-MBS networks.
  • The hybrid ISA-PSO algorithm effectively optimizes UAV-MBS 3D positioning and transmission power.
  • The weather-aware simulator enhances the practicality and reliability of UAV-MBS deployment strategies.