Quickest Spectrum Awareness under Correlated Spatio-temporal Variations

无线通信技术正在迅速超越其主要应用(例如蜂窝通信)，并在影响不同技术、社会和经济领域的各种新兴新技术中扮演着关键骨干的变革性角色。所有这些技术都是可行的，但代价是对无线电频谱不断增长的需求，而无线电频谱是无线行业的关键商品。要实现长期和可持续的无线基础设施，必须采用能够提高频谱接入效率并允许进行实时和细粒度频谱管理的技术。频谱管理的有效性关键取决于对跨时间和空间的频谱占用状态形成灵活而准确的情景感知。本研究项目的重点是开发一个全面的分析框架，以形成对无线频谱机会的时空变化的情景感知。该框架建立了与感测电路的双向交互。在前向，它接收传感器收集的测量结果，以形成各种检测、推理和资源管理决策。在相反的方向上，基于被认为是提供准确的态势感知所需的数据，它向传感器发送指令，指示如何继续从频谱的不同部分收集数据。由该框架形成的决策也可用于可视化决策和警报。该项目的研究任务包括：开发一个完整的框架，该框架连贯地集成了创新频谱感知的几个关键组件，形成了灵活的推理决策，实现了动态环境下的快速计算和快速自适应，并确保了环境不确定性下的决策稳健性。在每个推力中，该项目追求以下两个相互交织的研究目标：(1)理论基础：第一个目标是建立形成最快态势感知的基本限制，同时认识到由于感知成本、通信延迟容忍度、模型不确定性以及频谱感知受益者的动态变化而造成的物理约束，频谱感知涵盖了在不同协议和基础设施下运行的各种自主无线应用。(2)算法设计：第二个目标是设计数据分析工具和机制来形成最快的态势感知，它服从于实时和可扩展的实施，表现出良好的决策保证，并且完全适应和响应宽带频谱中频谱占用状态的时空变化。该项目将产生一个决策理论框架，以形成对宽带频谱不同部分上的频谱占用状态的快速和可靠的态势感知。为了实现这一目标，该项目将解决在最快检测网络数据变化方面的长期悬而未决的问题，受控感知中的公开问题，以及由频谱感知的物理限制引发的挑战性问题，例如1)感知预算，2)模型不确定性下的决策，以及3)试图危害感知数据和扭曲频谱感知决策的对手。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Wireless communication technology is rapidly transcending its primary applications (e.g., cellular communications) and plays a transformative role as the critical backbone in various emerging new technologies that affect different technological, social, and economic domains. All such technologies are viable at the expense of increasing demands for radio spectrum, which is the key commodity in the wireless industry. Enabling long-term and sustainable wireless infrastructures necessitates technologies that enhance spectrum access efficiency and allow for real-time and fine-granularity spectrum management. The effectiveness of spectrum management critically depends on forming agile and accurate situational awareness of spectrum occupancy states across time and space. This research project focuses on developing a comprehensive analytical framework for forming situational awareness of the spatio-temporal variations in wireless spectrum opportunities. This framework establishes bi-directional interactions with the sensing circuitry. In the forward direction, it receives measurements collected by the sensors in order to form various detection, inferential, and resource management decisions. In the reverse direction, based on the data deemed necessary for delivering accurate situational awareness, it sends instructions to the sensors on how to proceed with collecting data from various segments of the spectrum. The decisions formed by this framework can also be used for visualizing decisions and alarms. The research tasks of this project include: developing a comprehensive framework that coherently integrates several critical components for innovative spectrum sensing, forming agile inferential decisions, achieving fast computations and fast adaptivity in dynamic settings, and ensuring decision robustness under environment uncertainties.To develop such a comprehensive framework, this project has several research thrusts, each addressing one aspect of the framework. In each thrust, the project pursues the following two intertwined research objectives: (1) Theoretical Foundations: The first objective is to establish the fundamental limits of forming quickest situational awareness, while recognizing the physical restraints due to the cost of sensing, communication delay tolerance, model uncertainties, and dynamic variations of the beneficiaries of spectrum sensing, which encompass various autonomous wireless applications that operate under distinct protocols and infrastructures. (2) Algorithm Design: Driven by the observations gained from the uncovered fundamental limits, the second objective is to design data analytic tools and mechanisms for forming the quickest situational awareness, which is amenable to real-time and scalable implementation, exhibiting sound decision guarantees, and fully adaptive and responsive to the spatio-temporal variations of the spectrum occupancy status in wideband spectrum. This project will produce a decision-theoretic framework for forming quick and reliable situational awareness of the spectral occupancy states over different segments in wideband spectrum. To achieve this goal, the project will address long-standing open problems in quickest detection of change over networked data, open problems in controlled sensing, as well as challenging problems motivated by the physical constraints of spectrum sensing such as 1) sensing budget, 2) decision-making under model uncertainty, and 3) detecting adversaries that seek to compromise sensing data and distort spectrum sensing decisions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.