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，共同使用无线频谱进行通信和传感。考虑的环境将是新兴蜂窝网络，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，这项研究将带来更好的连接和更高的用户数据速率，并改进通过雷达技术定位和跟踪移动用户的传感。因此，这些技术将使新的智慧城市服务和应用成为可能。在教育方面，该项目将导致开发新的教育材料。针对初中生和高中生的外展活动将通过广泛普及的系列讲座进行。拟议的活动将特别注重促进多样性和培养学生人才。最后，结果将通过德克萨斯大学奥斯汀分校无线网络和通信集团(WNCG)的工业附属公司计划与业界分享。针对密集无线网络中基站和频谱资源的联合管理，提出了一种新的能量高效的跨层资源分配算法。同时，将引入基于随机几何的数学模型和工具，使人们能够表征和优化密集部署的能源性能。智能优势可以概括为四个方面：(A)通信和雷达/传感的基础设施和频谱共同使用，其中重点将放在处理通信和雷达波形混合干扰的算法上；(B)用于描述空间上不同频谱使用的随机几何模型和工具，其中将开发空间上的中央极限定理以表征SINR和雷达失真性能；(C)模式切换和基站激活的算法，其中将开发网络管理的负载相关算法，该算法将认识到与基站的模式变化和激活状态相关的滞后成本；以及(D)通过定向关联来管理用户动态，以减少网络中的改变频率，这将导致管理算法在各种空间尺度上的收敛行为得到改善。

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.