Coverage Maximization of Heterogeneous UAV Networks

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

3 Scopus Citations
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Author(s)

  • Shuyue Li
  • Chaocan Xiang
  • Wenzheng Xu
  • Jian Peng
  • Zichuan Xu
  • Jing Li

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS 2023)
PublisherInstitute of Electrical and Electronics Engineers, Inc.
Pages120-130
ISBN (electronic)979-8-3503-3986-4
Publication statusPublished - 2023

Publication series

NameProceedings - International Conference on Distributed Computing Systems
Volume2023-July

Conference

Title43rd IEEE International Conference on Distributed Computing Systems (ICDCS 2023)
LocationSheraton Hong Kong & Towers
PlaceHong Kong
Period18 - 21 July 2023

Abstract

In this paper we study the deployment of a UAV (unmanned aerial vehicle) network that consists of multiple UAVs to provide emergent communication services to people trapped in a disaster area, where each UAV is equipped with a base station that has limited computing capacity and power supply, and thus can only serve a limited number of users. Unlike most existing studies focusing on homogenous UAVs, we consider the deployment of heterogeneous UAVs, where different UAVs have different computing capacities. We study a problem of deploying K heterogeneous UAVs in the air to form a connected UAV network such that the number of users served by the UAVs is maximized, subject to the constraint that the number of users served by each UAV is no greater than its service capacity, assuming that the maximum number of users can be served by a UAV is given. We then propose a novel (\sqrt{\frac{s}{K}})-approximation algorithm for the problem, where s is a given positive integer, e.g., s=3. We finally evaluate the performance of the approximation algorithm. Experimental results show that the number of users served by all UAVs in the approximate solution is improved by 22% compared with the solutions delivered by state-of-the-arts. © 2023 IEEE.

Research Area(s)

  • approximation algorithms, heterogeneous UAVs, UAV communication networks, UAV deployment problem

Citation Format(s)

Coverage Maximization of Heterogeneous UAV Networks. / Li, Shuyue; Xiang, Chaocan; Xu, Wenzheng et al.
Proceedings - 2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS 2023). Institute of Electrical and Electronics Engineers, Inc., 2023. p. 120-130 (Proceedings - International Conference on Distributed Computing Systems; Vol. 2023-July).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review