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Throughput Maximization of UAV Networks

  • Wenzheng Xu
  • , Yueying Sun
  • , Rui Zou
  • , Weifa Liang
  • , Qiufen Xia
  • , Feng Shan
  • , Tian Wang
  • , Xiaohua Jia
  • , Zheng Li*
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

In this paper we study the deployment of multiple unmanned aerial vehicles (UAVs) to form a temporal UAV network for the provisioning of emergent communications to affected people in a disaster zone, where each UAV is equipped with a lightweight base station device and thus can act as an aerial base station for users. Unlike most existing studies that assumed that a UAV can serve all users in its communication range, we observe that both computation and communication capabilities of a single lightweight UAV are very limited, due to various constraints on its size, weight, and power supply. Thus, a single UAV can only provide communication services to a limited number of users. We study a novel problem of deploying K UAVs in the top of a disaster area such that the sum of the data rates of users served by the UAVs is maximized, subject to that (i) the number of users served by each UAV is no greater than its service capacity; and (ii) the communication network induced by the K UAVs is connected. We then propose a 1-1/e/[√K]-approximation algorithm for the problem, improving the current best result of the problem by five times (the best approximation ratio so far is 1-1/e/5( √K +1)), where e is the base of the natural logarithm. We finally evaluate the algorithm performance via simulation experiments. Experimental results show that the proposed algorithm is very promising. Especially, the solution delivered by the proposed algorithm is up to 12% better than those by existing algorithms.
Original languageEnglish
Pages (from-to)881-895
Number of pages15
JournalIEEE/ACM Transactions on Networking
Volume30
Issue number2
Online published12 Nov 2021
DOIs
Publication statusPublished - Apr 2022

Research Keywords

  • Approximation algorithms
  • Base stations
  • Computer science
  • connected maximum throughput problem
  • distributed resource allocation and provisioning
  • emergent communication
  • IEEE transactions
  • Throughput
  • UAV networks
  • Unmanned aerial vehicles
  • Urban areas

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