Department of Computing and Technology, Iqra University, Islamabad 44000, Pakistan.
University Institute of Information Technology, PMAS-Arid Agriculture University, Rawalpindi 46000, Pakistan.
Sensors (Basel). 2022 Aug 16;22(16):6130. doi: 10.3390/s22166130.
Unmanned Aerial Vehicle (UAV) deployment and placement are largely dependent upon the available energy, feasible scenario, and secure network. The feasible placement of UAV nodes to cover the cellular networks need optimal altitude. The under or over-estimation of nodes' air timing leads to of resource waste or inefficiency of the mission. Multiple factors influence the estimation of air timing, but the majority of the literature concentrates only on flying time. Some other factors also degrade network performance, such as unauthorized access to UAV nodes. In this paper, the UAV coverage issue is considered, and a Coverage Area Decision Model for UAV-BS is proposed. The proposed solution is designed for cellular network coverage by using UAV nodes that are controlled and managed for reallocation, which will be able to change position per requirements. The proposed solution is evaluated and tested in simulation in terms of its performance. The proposed solution achieved better results in terms of placement in the network. The simulation results indicated high performance in terms of high packet delivery, less delay, less overhead, and better malicious node detection.
无人机(UAV)的部署和放置在很大程度上取决于可用能源、可行的场景和安全的网络。为了覆盖蜂窝网络,需要选择最佳的 UAV 节点放置高度。节点空中时间的低估或高估会导致资源浪费或任务效率低下。有多个因素会影响空中时间的估计,但大多数文献仅集中在飞行时间上。其他一些因素也会降低网络性能,例如对无人机节点的未授权访问。在本文中,考虑了无人机覆盖问题,并提出了一种无人机基站的覆盖区域决策模型。所提出的解决方案旨在通过使用可控制和管理的无人机节点来实现蜂窝网络覆盖,这些节点可以根据需要进行重新分配和位置更改。所提出的解决方案在仿真中进行了评估和测试,以评估其性能。在所提出的解决方案中,在网络中的放置方面取得了更好的结果。仿真结果表明,在高分组投递率、低延迟、低开销和更好的恶意节点检测方面具有更高的性能。