CRII: CIF: Towards Self-Powered Heterogeneous Cellular Networks

在移动的数据流量的空前增长的驱动下，蜂窝网络正在经历从高功率小区塔（基站）的以覆盖为中心的同质部署到更有机的容量驱动的部署的巨大范式转变，所述更有机的容量驱动的部署另外包括各种类型的低功率基站，统称为小小区。为了保持部署灵活性并限制运营成本，非常希望这些基站具有通过自包含的能量收集模块为自身供电的能力。然而，与能量收集相关联的固有的不可靠性，结合小小区的不规则位置，使得量化这种“自供电”异构蜂窝网络的可靠性具有挑战性。该项目旨在通过新的分析工具和指标为这些网络奠定基础。具有额外的自回程能力的自供电基站将导致“真正的无线”蜂窝网络，从而实现各种“丢弃和播放”部署。该项目将通过研究传播、教育、扩大学生参与和行业合作产生更广泛的影响。该项目的总体目标是为自供电异构网络建立基本性能限制，采用了一种跨学科的方法，涉及通信，信息论和随机几何学的工具。该项目的第一个协同组件开发了一个新的综合模型，能够捕获自供电异构网络的关键特征，例如基站能力的差异，部署的不规则性以及能量水平的不确定性。强大的数学工具，在随机几何和点过程理论的基础上，这个模型的易处理性，从而允许正式分析的新的性能指标独特的自供电异构网络。例如，由于基站之间的负载耦合，当一个基站耗尽其能量时，它可能会引发“级联效应”，使整个网络与之一起崩溃。第一组结果表征了这种行为，并确定了网络保持稳定的状态。一旦稳定性得到保证，第二组结果就集中在这种新范例中的终端用户性能上，其中幸存的基站并不总是保证具有足够的能量来服务于其所有负载，从而导致能量中断。最后，将这些指标与经典的体验质量指标（如下行链路速率）进行联合分析。

Driven by unprecedented increase in mobile data traffic, cellular networks are undergoing a huge paradigm shift from a coverage-centric homogeneous deployment of high-power cell towers (base stations) to a more organic capacity-driven deployment that additionally includes various types of low-power base stations, collectively called small cells. To maintain deployment flexibility and limit operational costs, it is highly desirable that these base stations have a capability to power themselves through self-contained energy harvesting modules. The inherent unreliability associated with energy harvesting, however, combined withthe irregular locations of the small cells, makes it challenging to quantify the reliability of such "self-powered" heterogeneous cellular networks. This project aims to lay the foundations of these networks through new analytical tools and metrics. Self-powered base stations with additional capability to self-backhaul will result in a "truly wireless" cellular network thereby enabling a variety of "drop and play" deployments. Further broader impact of this project will be through research dissemination, education, broadening participation of students, and industry collaboration. With the overarching goal of establishing fundamental performance limits for self-powered hetergeneous networks, this project adopts a cross-disciplinary approach involving tools from communications, information theory, and stochastic geometry. The first synergistic component of this project develops a new comprehensive model capable of capturing key characteristics of self-powered heterogeneous networks, such as the differences in the base station capabilities, irregularities in their deployments, and uncertainties in their energy levels. Powerful mathematical tools with foundations in stochastic geometry and point process theory lend tractability to this model, thereby allowing the formal analysis of new performance metrics unique to self-powered heterogeneous networks. For instance, due to the coupling of loads across base stations, when one base station drains out its energy, it may initiate a "cascade effect" taking the whole network down with it. The first suite of results characterizes this behavior and determines the regimes in which the network remains stable. Once stability is guaranteed, the second set of results focuses on the end-user performance in this new paradigm where the surviving base stations are not always guaranteed to have sufficient energy to serve all their load, thereby resulting in energy outages. Finally, these metrics are jointly analyzed with classical quality-of-experience metrics, such as downlink rate.