Towards 3D Deployment of UAV Base Stations in Uneven Terrain

Xiaofei He, Wei Yu, Hansong Xu, Jie Lin, Xinyu Yang, Chao Lu, Xinwen Fu
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引用次数: 29

Abstract

Unmanned Aerial Vehicles (UAVs), also known as drones, have become a new paradigm to provide emergency wireless communication infrastructure when conventional base stations are damaged or unavailable. In this paper, we propose new schemes to enable the 3D deployment of drones, which can provide network coverage and connectivity services for users located in uneven terrain. We formalize two models, including optimal coverage model and optimal connectivity model, which belong to NP-hard. To be specific, we first consider both the quality of service (QoS) requirements of users and the capacity of drones. We then formalize the problem and design a heuristic scheme, called Particle Swarm Optimization (PSO) algorithm to achieve a cost-effective solution. We also address the optimal connectivity problem in a scenario, in which a number of isolated local networks have been established by users through ad hoc communication and/or device-to-device (D2D) communication. We further develop the cost-effective heuristic algorithm to effectively minimize the total number of required drones. Via extensive performance evaluation, our experimental results demonstrate that the proposed schemes can achieve the effective deployment of drones for users in uneven terrain with respect to the number of required drones.
不平坦地形下无人机基站三维部署研究
无人驾驶飞行器(uav)也被称为无人机,已成为在传统基站损坏或不可用时提供应急无线通信基础设施的新范例。在本文中,我们提出了新的方案来实现无人机的3D部署,它可以为位于不平坦地形的用户提供网络覆盖和连接服务。我们形式化了两个模型,包括最优覆盖模型和最优连通性模型,它们属于NP-hard。具体来说,我们首先考虑用户的服务质量(QoS)需求和无人机的容量。然后,我们将问题形式化并设计了一种启发式方案,称为粒子群优化(PSO)算法,以实现成本效益的解决方案。我们还解决了一个场景中的最佳连接问题,在这个场景中,用户通过自组织通信和/或设备对设备(D2D)通信建立了许多孤立的本地网络。我们进一步开发了具有成本效益的启发式算法,以有效地减少所需无人机的总数。通过广泛的性能评估,我们的实验结果表明,就所需无人机的数量而言,我们提出的方案可以为不平坦地形的用户实现有效的无人机部署。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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