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On the Association of Small Cell Base Stations with UAVs Using Unsupervised Learning

机译:用无人机使用无人机学习与小型电池基站的关联

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Small cell networks (SCNs) offer a cost-effective coverage solution to wireless applications demanding high data rates. However in SCNs, a challenging problem is the proper management of backhaul links to small cell base stations (SCBSs). To make a good backhaul link, perfect line-of-sight (LoS) communication between the SCBSs and the core network plays a vital role. In this study, we use the idea of employing unmanned aerial vehicles (UAVs) to provide connectivity between SCBSs and the core network. We focus on the association of SCBSs with UAVs by considering multiple communication-related factors including data rate limit and available bandwidth resources of the backhaul. In particular, we address the optimum placement of UAVs to serve a maximum number of SCBSs while considering available resources using unsupervised extit{k}- means algorithm. Numerical results show that the proposed approach outperforms the conventional approach in terms of associated SCBSs, bandwidth consumption, available link utilization, and sum- rate maximization.
机译:小单元网络(SCNS)为要求高数据速率的无线应用提供经济高效的覆盖解决方案。然而,在SCNS中,一个具有挑战性的问题是对小型小区基站(SCBS)的正回力链接的适当管理。为了使良好的回程链路,SCBS和核心网络之间的完美视线(LOS)通信起着重要作用。在这项研究中,我们使用采用无人驾驶飞行器(无人机)的想法来提供SCBS和核心网络之间的连接。我们通过考虑多次通信相关的因素,专注于SCBS与无人机的关联,包括数据速率限制,以及回程的可用带宽资源。特别是,我们解决了无人机的最佳放置,以使用无监督 Textit {k}算法考虑可用资源的同时满足最大数量的SCBS。数值结果表明,该方法在相关的SCBS,带宽消耗,可用链路利用率和SUM率最大化方面优于传统方法。

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