TY - JOUR
T1 - Throughput Maximization of UAV Networks
AU - Xu, Wenzheng
AU - Sun, Yueying
AU - Zou, Rui
AU - Liang, Weifa
AU - Xia, Qiufen
AU - Shan, Feng
AU - Wang, Tian
AU - Jia, Xiaohua
AU - Li, Zheng
PY - 2022/4
Y1 - 2022/4
N2 - 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.
AB - 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.
KW - Approximation algorithms
KW - Base stations
KW - Computer science
KW - connected maximum throughput problem
KW - distributed resource allocation and provisioning
KW - emergent communication
KW - IEEE transactions
KW - Throughput
KW - UAV networks
KW - Unmanned aerial vehicles
KW - Urban areas
UR - http://www.scopus.com/inward/record.url?scp=85119439123&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85119439123&origin=recordpage
U2 - 10.1109/TNET.2021.3125982
DO - 10.1109/TNET.2021.3125982
M3 - 21_Publication in refereed journal
VL - 30
SP - 881
EP - 895
JO - IEEE - ACM Transactions on Networking
JF - IEEE - ACM Transactions on Networking
SN - 1063-6692
IS - 2
ER -