UAV Deployment Design Under Incomplete Information with a Connectivity Constraint for UAV-Assisted Networks

Takumi Sakamoto, Tomotaka Kimura and Kouji Hirata ()
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Takumi Sakamoto: Graduate School of Science and Engineering, Kansai University, Osaka 564-8680, Japan
Tomotaka Kimura: Faculty of Science and Engineering, Doshisha University, Kyoto 610-0321, Japan
Kouji Hirata: Faculty of Engineering Science, Kansai University, Osaka 564-8680, Japan

Future Internet, 2025, vol. 17, issue 9, 1-19

Abstract: In this paper, we introduce an Unmanned Aerial Vehicle (UAV) deployment design with a connectivity constraint for UAV-assisted communication networks. In such networks, multiple UAVs are collaboratively deployed in the air to form a network that realizes efficient relay communications from ground mobile clients to the base station. We consider a scenario where ground clients are widely distributed in a target area, with their population significantly outnumbering available UAVs. The goal is to enable UAVs to collect and relay all client data to the base station by continuously moving while preserving end-to-end connectivity with the base station. To achieve this, we propose two dynamic UAV deployment methods: genetic algorithm-based and modified ε -greedy algorithm-based methods. These methods are designed to efficiently collect data from mobile clients while maintaining UAV connectivity, based solely on local information about nearby client positions. Through numerical experiments, we demonstrate that the proposed methods dynamically form UAV-assisted networks to efficiently and rapidly collect client data transmitted to the base station.

Keywords: UAV-assisted network; UAV deployment design; Genetic algorithm; ε-greedy algorithm (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2025
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