MEC-assisted Dynamic Geofencing for 5G-enabled UAV

被引:3
作者
Bera, Abhishek [1 ]
Sanchez-Cuevas, Pedro J. [1 ]
Olivares-Mendez, Miguel Angel [1 ]
机构
[1] Univ Luxembourg, Interdisciplinary Ctr Secur Reliabil & Trust SnT, Luxembourg, Luxembourg
来源
2022 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC) | 2022年
关键词
Unmanned Aerial Vehicle (UAV); Mobile Edge Computing (MEC); 5G; Fast Marching Method (FMM); Geofence; 3D; 5G;
D O I
10.1109/WCNC51071.2022.9771716
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
5G-enabled UAV-based services have become popular for civilian applications. At the same time, certain no-fly zones will be highly dynamic, e.g. accident areas, large outdoor public events, VIP convoys etc. An appropriate geofencing algorithm is required to avoid the no-fly zone in such scenarios. However, it is challenging to execute a high computing process such as a geofencing algorithm for a resource constraint UAV. This paper proposes an architecture and a geofencing algorithm for 5G-enabled UAV using Mobile Edge Computing (MEC). Also, the 5G-enabled UAV must fly within the coverage area during a mission. Hence, there must be an optimal trade-off between 5G coverage and distance to travel to design a new trajectory for a 5G-enabled UAV. To this end, we propose a cost minimization problem to generate a new trajectory while a no-fly zone exists. Specifically, we design a cost function considering 5G coverage and the velocity of the UAV. Then, we propose a geofencing algorithm running at the MEC by adopting the fast marching method (FMM) to generate a new trajectory for the UAV. Finally, a numerical example shows how the proposed geofencing algorithm generates an optimal trajectory for a UAV to avoid a dynamically created no-fly zone while on the mission.
引用
收藏
页码:160 / 165
页数:6
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