Multicriteria UAV Base Stations Placement for Disaster Management

被引:43
|
作者
Akram, Tallha [1 ]
Awais, Muhammad [1 ]
Naqvi, Rameez [1 ]
Ahmed, Ashfaq [1 ]
Naeem, Muhammad [1 ]
机构
[1] COMSATS Univ Islamabad, Elect & Comp Engn Dept, Wah Campus, Wah 47040, Pakistan
来源
IEEE SYSTEMS JOURNAL | 2020年 / 14卷 / 03期
关键词
Drones; Optimization; Wireless communication; Feature extraction; Mathematical model; Complexity theory; Base stations; Cellular networks; neural networks; optimization; unmanned aerial vehicles (UAVs); 3-D PLACEMENT;
D O I
10.1109/JSYST.2020.2970157
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In disaster situations, collapse of local communication infrastructure is a major issue due to destruction of buildings, antennas, power sources, and to name a few. Drones, as flying base stations, are a promising solution to restore essential communication services in emergency situations. The contribution of this article is twofold: First, an efficient computer vision technique is proposed to identify areas with high density of low mobility or stationary users. This is done using a multistep process, which includes image acquisition, classification, and crowd density estimation. Next, an accurate mathematical model is presented for joint optimization of drone base stations placement and user assignment. The goal here is to maximize the number of serviced users with minimum number of drones, while satisfying practical network constraints. An optimal solution to such a biobjective optimization problem has complexity exponential to the network size. Furthermore, a low complexity heuristic is proposed to solve the optimization problem. Complexity analysis of the proposed solution is then carried out. Simulation results for a number of practical network scenarios demonstrate that the proposed solution achieves a performance comparable to the optimal solution.
引用
收藏
页码:3475 / 3482
页数:8
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