Joint Optimization of UAV Deployment and Directional Antenna Orientation for Multi-UAV Cooperative Sensing

被引:0
作者
Zhou, Lingyun [1 ]
Pu, Wenqiang [2 ]
You, Ming-yi [3 ]
Zhang, Rongqing [1 ]
Shi, Qingjiang [1 ,2 ]
机构
[1] Tongji Univ, Sch Software Engn, Shanghai 201804, Peoples R China
[2] Shenzhen Res Inst Big Data, Shenzhen 518172, Peoples R China
[3] Sci & Technol Commun Informat Secur Control Lab, Jiaxing 314033, Peoples R China
来源
2023 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, WCNC | 2023年
关键词
UAV deployment; antenna orientation; sensing system; energy detection; Gibbs sampling; ENERGY DETECTION;
D O I
10.1109/WCNC55385.2023.10118837
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we consider the problem of cooperative sensing via a system of multi-unmanned aerial vehicles (UAVs), where each UAV is equipped with a directional antenna to cooperatively perform detection tasks for several targets of interest. To measure the perception ability of the system, we choose the detection probability as the metric, aiming to maximize the sum detection probability of targets by jointly optimizing UAVs' deployment and directional antenna orientations. To tackle the inherent nonconvexity of the formulated problem, we first decompose it into two sub-problems, i.e., a slave problem for optimizing the antenna orientations with a given UAVs' deployment, and a master problem for optimizing the UAVs' deployment. By virtue of the slave problem structure, an efficient block coordinate descent (BCD) algorithm is developed. Meanwhile, to deal with the lack of the closed expression of the sum detection probability with respect to the UAVs' deployment, we further develop an iterative algorithm to acquire an efficient solution with the aid of Gibbs Sampling (GS) approach. Extensive simulations demonstrate the efficacy of the proposed algorithm.
引用
收藏
页数:5
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