CNS Core: Small: Collaborative: Towards Surge-Resilient Hybrid RF/VLC Networks

智能城市规模的无线服务，如物联网（IoT）的成功部署，取决于可靠的通信基础设施的存在，这种基础设施可以普遍连接人和机器类型的设备。为了支持物联网生态系统的预期流量，无线基础设施必须能够适应从热点事件和随机故障到自然灾害和有针对性攻击等大量事件可能导致的流量激增。这项研究的目标是开发一种新的无线网络架构，利用射频（RF）和可见光通信（VLC）来提供弹性和无处不在的连接。开发的架构和相关框架将汇集来自通信理论、学习和博弈论的新颖跨学科思想，以探索混合弹性RF/VLC网络的基本理论和实验挑战。这项研究与一项全面的教育计划相结合，该计划包括新的课程材料、教程，以及研究生和本科生大规模参与与弹性通信和网络相关的研究。本研究将引入一种新的框架，用于设计、分析和优化RF/VLC混合通信，以应对故障、热点和自然灾害。关键技术贡献将包括：1)针对RF/VLC系统量身定制的新颖调度算法，可以在流量激增的情况下最大限度地增加可用连接的用户数量；2)基于非正交多址的有效传输机制，提高快闪人群的频谱效率；3)基于博弈论和强化学习的弹性自组织算法，利用无线电接入技术的反馈，在信息不完整的情况下实现智能和弹性的资源管理；4)实际RF/VLC实验，将用于验证所提出的研究并弥合理论与实践之间的差距。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The successful deployment of smart city-scale wireless services, such as the Internet of Things (IoT), hinges on the presence of a reliable communication infrastructure that can pervasively connect both human and machine-type devices. In order to support the traffic anticipated from an IoT ecosystem, the wireless infrastructure must be resilient to the surge of traffic that can result from a plethora of events that range from hot-spot events and random failures to natural disasters and targeted attacks. The goal of this research is to develop a novel wireless network architecture that leverages both radio frequency (RF) and visible light communication (VLC) to provide resilient and pervasive connectivity. The developed architecture and associated frameworks will bring together novel, cross-disciplinary ideas from communication theory, learning, and game theory to explore the fundamental theoretical and experimental challenges of a hybrid and resilient RF/VLC network. The research is coupled with a comprehensive educational plan that includes new course material, tutorials, and large-scale involvement of graduate and undergraduate students in research related to resilient communications and networking.This research will introduce a novel framework for designing, analyzing, and optimizing hybrid RF/VLC communications, in the presence of failures, hotspots, and natural disasters. The key technical contributions will include: 1) Novel scheduling algorithms uniquely tailored towards RF/VLC systems that can maximize the number of users with available connectivity, in the presence of traffic surges; 2) Effective transmission mechanisms based on non-orthogonal multiple access that can enhance the spectral efficiency of flash crowds; 3) Resilient self-organizing algorithms, based on game theory and reinforcement learning, that exploit feedback across radio access technologies to enable intelligent and resilient resource management in the presence of incomplete information; and 4) Practical RF/VLC experiments that will be used to validate the proposed research and bridge the gap between theory and practice.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.