Energy-Efficient Drone Trajectory Planning for the Localization of 6G-Enabled IoT Devices

被引:25
|
作者
Kouroshnezhad, Sahar [1 ]
Peiravi, Ali [2 ]
Haghighi, Mohammad Sayad [3 ]
Jolfaei, Alireza [4 ]
机构
[1] Islamic Azad Univ, Dept Elect Engn, Bojnourd Branch, Bojnourd 9417697796, Iran
[2] Ferdowsi Univ Mashhad, Elect Engn Dept, Mashhad 9177948974, Razavi Khorasan, Iran
[3] Univ Tehran, Coll Engn, Sch Elect & Comp Engn, Tehran 1439957131, Iran
[4] Macquarie Univ, Dept Comp, Sydney, NSW 2109, Australia
关键词
Drones; Trajectory; Heuristic algorithms; Intelligent sensors; 6G mobile communication; 6G; advanced sensors; drone; dynamic path planning; energy efficiency; Internet of Things (IoT); localization;
D O I
10.1109/JIOT.2020.3032347
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
6G will be an enabler for the massive Internet of Things (IoT) in which millions of devices communicate at high data rates and low latencies. One key area among 6G applications is advanced sensing. However, higher speed implies moving to higher frequencies, which generally require more transmission power. In remote sensing, this causes problems, since either we have to increase the number of sensors and lower their communications ranges or increase their ranges and accept faster battery depletion. To cut the cost, even localization modules are not usually included in sensors. However, in many applications, IoT sensors must know their locations. Recent advances in the field of drones have led to promising solutions for localization. In this article, we propose a novel approach called semidynamic mobile anchor guiding (SEDMAG) for drones which aims at energy-conservative trajectory planning and localization of massive IoT devices. In this approach, the drone tracks the shortest path over a connected graph. This path determines the visiting order of devices. But we show that the complexity of this approach is high, thus, a graph reduction approach is proposed. It reduces the complexity and decreases the drones' energy consumption and positioning delay. The drone then follows a weighted search algorithm (WSA) to dynamically visit the devices. Simulation results are used to verify the superiority of the proposed approach.
引用
收藏
页码:5202 / 5210
页数:9
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