Service Time Maximization for Data Collection in Multi-UAV-Aided Networks

被引:4
作者
Dandapat, Jyotirindra [1 ]
Gupta, Nishant [2 ]
Agarwal, Satyam [3 ]
Kumbhani, Brijesh [3 ]
机构
[1] IIT Delhi, Dept Elect Engn, Delhi 110016, India
[2] Linkoping Univ, Dept Elect Engn, S-58183 Linkoping, Sweden
[3] IIT Ropar, Dept Elect Engn, Ropar 140001, India
来源
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES | 2024年 / 9卷 / 01期
关键词
Trajectory; Mobile nodes; Autonomous aerial vehicles; Wireless networks; Resource management; Data collection; Energy consumption; Energy management; mobile nodes; Multi-UAV-aided wireless networks; multi-UAV trajectory; resource management; COMMUNICATION DESIGN; RESOURCE-ALLOCATION; MINIMIZATION;
D O I
10.1109/TIV.2023.3287629
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Unmanned aerial vehicles (UAVs) have been enormously gaining attention to offload traffic or collect data in wireless networks due to their key attributes, such as mobility, flexibility, and cost-effective deployment. However, the limited onboard energy inhibits the UAV from serving for a longer duration. Therefore, this article studies a UAV-aided network where multiple UAVs are launched to collect data from the mobile nodes. In particular, we aim to maximize the service time of the UAVs by jointly optimizing the three-dimensional (3D) trajectory of the UAVs and resources allocated to each node by the UAVs such that each mobile node receives a minimum specified data rate. To facilitate a solution, we construct an equivalent problem that considers the UAV's energy consumption. In particular, we minimize the maximum energy consumed by the UAVs in each time slot. To solve the problem, an iterative approach is presented that decouples the problem into two sub-problems. The optimal location of the UAVs is computed in the first sub-problem, while resource allocation is carried out in the second sub-problem. These two sub-problems are solved in an iterative manner using the alternating optimization approach. We show that the proposed approach improves the service time of the network by 20% on average compared to the existing approaches.
引用
收藏
页码:328 / 337
页数:10
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