Dynamic Multi-Modal UAV Control for Optimized Coverage and Backhaul Connectivity in Spatially Unstructured and Dispersed User Environments

Unmanned aerial vehicles (UAVs) have emerged as a promising solution for establishing wireless communications in regions lacking terrestrial network infrastructure, such as remote or emergency areas. Deploying UAV networks effectively in these scenarios poses significant challenges due to the unknown and potentially complex locations of users. In scenarios where users are dispersed in intricate spatial patterns, achieving high coverage and resilient network connectivity among the UAV networks is challenging. The irregular and arbitrary distribution of users can lead to gaps in coverage, as traditional UAV placement optimization approaches are often unable to adapt to such dynamic environments. This complexity necessitates advanced strategies to ensure reliable and continuous network service to users. In this paper, we propose a distributed approach that leverages flocking dynamics and distributed consensus algorithms for dynamic UAV positioning. By enabling a multi-modal UAV operation policy, we develop a framework which enables the network to dynamically respond to complex user locations and establish backhaul connectivity between dispersed user clusters. Simulation results demonstrate that our approach successfully establishes a robust and adaptable UAV network capable of providing seamless coverage for complex user configurations and also ensuring comprehensive inter-cluster connectivity among dispersed user clusters. Additionally, the network exhibits strong resilience against random failures, swiftly recovering from disruptions to ensure stable and reliable communication even when UAVs are compromised.

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Publication Details

Journal
IEEE Transactions on Mobile Computing
Published
2025-09-05
DOI
https://doi.org/10.1109/tmc.2025.3606778
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Dynamic Multi-Modal UAV Control for Optimized Coverage and Backhaul Connectivity in Spatially Unstructured and Dispersed User Environments

Yuhui Wang, Junaid Farooq, Juntao Chen
IEEE Transactions on Mobile Computing
Distributed Control Multi-Agent Systems
article

Dynamic Multi-Modal UAV Control for Optimized Coverage and Backhaul Connectivity in Spatially Unstructured and Dispersed User Environments

Yuhui Wang, Junaid Farooq, Juntao Chen
article en

Abstract

Unmanned aerial vehicles (UAVs) have emerged as a promising solution for establishing wireless communications in regions lacking terrestrial network infrastructure, such as remote or emergency areas. Deploying UAV networks effectively in these scenarios poses significant challenges due to the unknown and potentially complex locations of users. In scenarios where users are dispersed in intricate spatial patterns, achieving high coverage and resilient network connectivity among the UAV networks is challenging. The irregular and arbitrary distribution of users can lead to gaps in coverage, as traditional UAV placement optimization approaches are often unable to adapt to such dynamic environments. This complexity necessitates advanced strategies to ensure reliable and continuous network service to users. In this paper, we propose a distributed approach that leverages flocking dynamics and distributed consensus algorithms for dynamic UAV positioning. By enabling a multi-modal UAV operation policy, we develop a framework which enables the network to dynamically respond to complex user locations and establish backhaul connectivity between dispersed user clusters. Simulation results demonstrate that our approach successfully establishes a robust and adaptable UAV network capable of providing seamless coverage for complex user configurations and also ensuring comprehensive inter-cluster connectivity among dispersed user clusters. Additionally, the network exhibits strong resilience against random failures, swiftly recovering from disruptions to ensure stable and reliable communication even when UAVs are compromised.

IEEE Transactions on Mobile ComputingVol. 25(2)
Fordham University (US), University of Michigan–Dearborn (US)
Openalex Percentile: Top 73%
Distributed Control Multi-Agent Systems
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