[论文解读] Blocking Probability and Spatial Throughput Characterization for Cellular-Enabled UAV Network with Directional Antenna

Jiangbin Lyu, Rui Zhang|arXiv (Cornell University)|Oct 28, 2017

UAV Applications and Optimization参考文献 11被引用 17

一句话总结

本文提出了一种在蜂窝网络中用于无人机的定向波束方案，以减少同频干扰并提高频谱效率。通过将无人机和基站的位置建模为独立的泊松点过程，推导出无人机阻塞概率的紧致闭式上界，并表征空间吞吐量，结果表明优化无人机高度和波束宽度可显著降低阻塞概率并提升网络性能。

ABSTRACT

The past few years have witnessed a tremendous increase on the use of unmanned aerial vehicles (UAVs) in civilian applications, which call for high-performance communication between UAVs and their ground clients, especially when they are densely deployed. To achieve this goal, cellular base stations (BSs) can be leveraged to provide a new and promising solution to support massive UAV communications simultaneously in a cost-effective way. However, different from terrestrial communication channels, UAV-to-BS channels are usually dominated by the light-of-sight (LoS) link, which aggravates the co-channel interference and renders the spatial frequency reuse in existing cellular networks ineffective. In this paper, we consider the use of a directional antenna at each UAV to confine the interference to/from other UAV users within a limited region and hence improve the spatial reuse of the spectrum. Under this model, a UAV user may be temporarily blocked from communication if it cannot find any BS in its antenna main-lobe, or it finds that all BSs under its main-lobe are simultaneously covered by those of some other UAVs and hence suffer from strong co-channel interference. Assuming independent homogeneous Poisson point processes (HPPPs) for the UAVs' and ground BSs' locations respectively, we first analytically derive a closed-form upper bound for the UAV blocking probability and then characterize the achievable average spatial throughput of the cellular-enabled UAV communication network, in terms of various key parameters including the BS/UAV densities as well as the UAV's flying altitude and antenna beamwidth. Simulation results verify that the derived bound is practically tight, and further show that adaptively adjusting the UAV altitude and/or beamwidth with different BS/UAV densities can significantly reduce the UAV blocking probability and hence improve the network spatial throughput.

研究动机与目标

• 为解决在视 Line-of-Sight（LoS）链路增加干扰的密集蜂窝网络无人机场景中的同频干扰挑战。
• 通过在无人机上使用定向波束，将干扰限制在有限区域，从而提升频谱复用效率。
• 对因主瓣内无可用基站或受其他无人机干扰而导致的无人机通信阻塞概率进行建模与量化。
• 表征在不同无人机/基站密度、高度和波束宽度下无人机网络的平均空间吞吐量。
• 优化无人机高度与波束宽度，以最小化阻塞概率并最大化空间吞吐量。

提出的方法

• 将无人机和地面基站的位置建模为独立的齐次泊松点过程（HPPPs）。
• 在每架无人机上使用具有固定波束宽度的定向波束，以将通信限制在由波束宽度和高度定义的地面覆盖区域。
• 基于无人机主瓣覆盖区内无专属基站可用的概率，推导出无人机阻塞概率的闭式上界。
• 以基站密度、无人机密度、高度和波束宽度为参数，表征可实现的平均空间吞吐量。
• 采用蒙特卡洛模拟估计当 L ≥ 2 时重叠无人机覆盖区域的参数 αₗ 和 βₗ。
• 通过大量仿真验证分析边界，确认阻塞概率上界和空间吞吐量下界均具有紧密性。

实验结果

研究问题

• RQ1 在蜂窝网络无人机系统中，无人机使用定向波束如何影响阻塞概率？
• RQ2 无人机高度与波束宽度对阻塞概率与空间吞吐量有何影响？
• RQ3 在定向波束成形下，基站与无人机密度如何影响可实现的空间吞吐量？
• RQ4 能否在泊松分布的无人机与基站网络中，为无人机阻塞概率推导出闭式上界？
• RQ5 所推导的空间吞吐量下界与仿真结果相比有多紧密？

主要发现

• 仿真结果验证了无人机阻塞概率的推导上界在各种无人机与基站密度下均具有实际紧密性。
• 根据网络密度自适应调节无人机高度与波束宽度，可显著降低阻塞概率并提升空间吞吐量。
• 空间吞吐量随波束宽度单调增加至某一点后，由于重叠无人机之间的干扰增加而性能下降，表明存在最优波束宽度。
• 在固定无人机高度下，较小波束宽度可提高方向性增益，但因覆盖区域减小而提高阻塞概率；较大波束宽度则增加干扰风险。
• 所提出的空间吞吐量下界与仿真结果高度吻合，尤其在阻塞概率随波束宽度增加而降低的区域表现更佳。
• 对 L ≥ 2 架无人机的 αₗ 和 βₗ 参数进行蒙特卡洛估计表明，随着重叠无人机数量增加，非重叠覆盖区域减小，从而影响阻塞概率。