SpecEES: Energy-efficient Spectrum and Infrastructure Co-use for Sensing and Communications in Dense Networks

该项目将开发新的节能技术，将无线频谱共同用于通信和传感。所考虑的设置将是新兴的蜂窝网络，由密集部署的基站（蜂窝塔上的无线基础设施）组成，提供重叠的无线覆盖。通过实现频谱的共同使用，这项研究将为用户带来更好的连接和更高的数据速率，并通过雷达技术改进定位和跟踪移动用户的传感。因此，这些技术将实现新的智慧城市服务和应用。在教育方面，该项目将导致新教材的开发。面向初高中学生的拓展活动将通过广泛的系列讲座进行。建议的活动将特别注重促进多元化和培养学生的才能。最后，研究结果将通过德克萨斯大学奥斯汀分校无线网络和通信小组（WNCG）的工业附属项目与工业界共享。提出的研究旨在开发一种新型节能跨层资源分配算法，用于密集无线网络中基站和频谱资源的联合管理。同时，将引入基于随机几何的数学模型和工具，使人们能够描述和优化密集部署的能源性能。智力上的优点可以概括为四个重点：(a)通信和雷达/传感的基础设施和频谱共同使用，其重点将是处理通信和雷达波形混合干扰的算法；(b)描述空间上异质频谱使用的随机几何模型和工具，其中将发展空间上的中心极限定理，以描述信噪比和雷达畸变性能；(c)模式转换和基站激活的算法，其中将开发网络管理的负荷相关算法，这些算法认识到与改变基站模式和激活状态有关的滞后费用；(d)通过定向关联来管理用户动态，以减少网络变化的频率，从而改善管理算法在不同空间尺度上的收敛行为。

This project will develop new energy-efficient techniques to co-use wireless spectrum for both communications and sensing. The setting considered will be that of emerging cellular networks consisting of a dense deployment of base-stations (wireless infrastructure on cell towers) providing overlapping wireless coverage. By enabling co-use of spectrum, this research will result in both better connectivity and improved data rates to users, and improved sensing through radar technologies for locating and tracking mobile users. These technologies will thus enable new smart city services and applications. On the educational front, the project will lead to development of new educational materials. Outreach activities to middle and high school students will occur through widely-accessible lecture series. The proposed activities will pay special attention to promoting diversity and nurturing student talent. Finally, the results will be shared with industry through the industrial affiliates program of the Wireless Networking and Communications Group (WNCG) at The University of Texas at Austin. The proposed research is geared at developing a new class of energy efficient cross-layer resource allocation algorithms for joint management of base-station and spectrum resources in dense wireless networks. At the same time, mathematical models and tools based on stochastic geometry will be introduced enabling one to characterize and optimize energy-performance for dense deployments. The intellectual merit can be summarized along four thrusts: (a) Infrastructure and spectrum co-use for communications and radar/sensing, where the focus will be on algorithms for handling interference from a mixture of communications and radar waveforms; (b) Stochastic geometry models and tools for characterizing heterogeneous spectrum use over space, where Central Limit Theorems over space will be developed to characterize SINR and radar distortion performance; (c) Algorithms for mode switching and base-station activation, where load-dependent algorithms for network management will be developed that are cognizant of hysteresis costs associated with changing modes and activation states of base-stations; and (d) Managing user dynamics through directed association to reduce the frequency of change in the network, which will result in improved convergence behavior of management algorithms at various spatial scales.