Unmanned aerial vehicle (UAV)-assisted communications have been regarded as a promising technology, which can be used in dynamic heterogeneous networks, since the UAVs can be applied as mobile base stations (MBSs). It is more efficient to set the UAVs as MBSs in different layers according to their functions. Due to the ability in communicating with other vehicles or facilities, vehicle-to-everything (V2X) makes the information required by the vehicles be efficiently transmitted and processed, so as to increase the safety of driving. However, because of the rapid change of topology and the huge demand of data transmission, it is hard to guarantee the efficient coverage of all the vehicles only by the support of terrestrial wireless communication networks. Considering this, this study combines UAV and V2X communications together, and proposes a multi-layer aerial-road vehicular (MLARV) architecture. The UAVs in the higher layer are in charge of overall monitoring, while the UAVs in the lower layer are responsible for hot-spot area coverage. To solve the throughput maximisation problem, the authors further propose a density-aware deployment (DAD) scheme with an iterative three-dimensional matching resource allocation algorithm. Simulation results show that the proposed DAD scheme with the MLARV architecture outperforms the traditional UAV-assisted V2X communications with single layer architecture.

中文翻译：

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多层UAV-V2X通讯网络的密度感知部署

由于无人机可以用作移动基站（MBS），因此无人飞行器（UAV）辅助通信已被视为有前途的技术，可用于动态异构网络。根据其功能将UAV设置为不同层的MBS效率更高。由于与其他车辆或设施进行通信的能力，车辆对所有车辆（V2X）使得车辆所需的信息得以有效地传输和处理，从而提高了驾驶的安全性。但是，由于拓扑结构的快速变化和数据传输的巨大需求，仅通过地面无线通信网络的支持就难以保证所有车辆的有效覆盖。考虑到这一点，本研究将无人机和V2X通信结合在一起，并提出了一种多层航空车（MLARV）架构。较高层的无人机负责总体监视，而较低层的无人机则负责热点区域的覆盖。为了解决吞吐量最大化问题，作者还提出了一种具有迭代三维匹配资源分配算法的密度感知部署（DAD）方案。仿真结果表明，所提出的具有MLARV体系结构的DAD方案优于具有单层体系结构的传统UAV辅助的V2X通信。作者还提出了一种具有迭代三维匹配资源分配算法的密度感知部署（DAD）方案。仿真结果表明，所提出的具有MLARV体系结构的DAD方案优于具有单层体系结构的传统UAV辅助的V2X通信。作者还提出了一种具有迭代三维匹配资源分配算法的密度感知部署（DAD）方案。仿真结果表明，所提出的具有MLARV体系结构的DAD方案优于具有单层体系结构的传统UAV辅助的V2X通信。