Heterogeneous Network Connectivity and Capacity

新兴一代无线网络的一个共同特征是它们的异构性：这些网络由具有非常不同的能力和需求的设备组成，共享重叠的频谱。由高清流媒体、游戏机、无线路由器和能源监控设备组成的智能家庭网络就是一个例子;认知网络（利用白色空间）和毫微微蜂窝网络是另外两个例子。 有点令人惊讶的是，几乎所有的工程设计，分析和知识是完全基于节点同质性的假设我们的研究涉及到获得基本的新的法律和限制异构无线网络的连接和容量。 这种限制的性质，预计将提供一个更好的设计principles.本研究的新奇是基于一个新的应用程序的标记点的过程，其中的点模型的节点位置和标记表征的节点的基本特征，如他们的带宽和功率。 为了计算所需的网络的统计特性，我们引入和推进新的数学工具，如Tauberian理论，随机函数系列，Stein近似理论和亚遍历理论。 除了该项目的基础研究方面，我们正在与几家领先的公司进行技术转让，开发异构网络，规划标准贡献和其他知识产权开发。 这与PI过去的跟踪记录一致。

A common characteristic of the emerging generation of wireless networks is their heterogeneity: these networks consist of devices with very different capabilities and requirements sharing overlapping spectrum. Intelligent home networks consisting of HD streaming, gaming consoles, wireless routers, and energy monitoring devices is one example; cognitive networks (utilizing white spaces), and femtocell networks being two more. Somewhat surprisingly, nearly all engineering design, analysis, and knowledge is based entirely on the assumption of node homogeneity Our research involves obtaining fundamental new laws and limits for the connectivity and capacity of heterogeneous wireless networks. The nature of such limits is expected to provide a roadmap for better design principles.The novelty of this research is based on a new application of marked point processes, where the points model the node locations and marks characterize essential traits of the node, like their bandwidth and power. To calculate the desired statistical properties of the network, we introduce and advance new mathematical tools such as Tauberian theory, series of random functions, Stein approximation theory, and sub-ergodic theory. In addition to the basic research aspect of this project, we are pursuing an energetic program of technology transfer with several leading companies developing heterogeneous networks and planning standards contributions and other intellectual property development. This is consistent with the PI's past track record.