Collaborative Research: SWIFT: Intelligent Dynamic Spectrum Access (IDEA): An Efficient Learning Approach to Enhancing Spectrum Utilization and Coexistence

随着无线连接对社会和经济互动的重要性日益增加，在只有接收机的无源系统对科学探索的安静频谱的关键要求中，对初级和次级有源无线电使用更多频谱的需求不断增加。为了提高无线生态系统的整体频谱利用率，本项目开发了一个整体的智能动态频谱接入（IDEA）框架，该框架可以大幅提高频谱共享网络的频谱利用率、能效和共存能力。在IDEA中，跨多个学科的技术创新得以协同发展，包括在设备和电路层面节能计算硬件的神经形态设计，以及在网络层面用于频谱传感和动态访问的人工智能。IDEA的频谱和干扰管理认真对待被动服务带来的共存限制，以支持遥感投资的科学和社会回报。预计此次研究成果将对自动驾驶、智慧城市、遥感等高流量需求的下一代无线网络和物联网应用产生广泛影响。该项目的目标是开发具有前所未有的频谱利用效率和敏捷性的智能动态频谱接入框架，以支持频谱共存。开发的IDEA网络平台支持来自主、次有源无线电和无源无线电的异构设备。在整个网络中进行关键技术创新，以大幅提高系统级频谱利用率和主动式无源无线电共存。具体来说，基于模拟/混合信号尖峰神经网络（SNN）的神经形态计算硬件旨在为资源受限的二次有源无线电提供超低功耗的机载智能。无模型深度强化学习与无线领域知识和SNN平台相结合，加速了基于学习的频谱接入和共存。先进的频谱监测技术被开发用于快速检测和表征各种有源和无源服务中的信号发射器。最后，开发了软件和硬件测试平台，用于系统级评估和权衡优化。IDEA框架不仅能在高度动态的无线环境中实现高效的频谱接入，还能促进跨设备和电路、传感和通信以及网络的整体系统设计和优化。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。

With the growing importance of wireless connectivity for social and economic interaction, there have been rising demands for greater spectrum use by both primary and secondary active radios, amidst the critical requirement of quiet spectrum for scientific exploration by receiver-only passive systems. To improve the overall spectrum utilization of the wireless ecosystem, this project develops a holistic Intelligent Dynamic spEctrum Access (IDEA) framework that can substantially enhance the spectrum utilization, energy-efficiency, and coexistence capability of spectrum sharing networks. In IDEA, enabling technical innovations across multiple disciplines are synergistically developed, including neuromorphic design of energy-efficient computing hardware at the device and circuit level, and artificial intelligence for spectrum sensing and dynamic access at the network level. The spectrum and interference management in IDEA conscientiously treats the coexistence constraints imposed by passive services, in support of scientific and societal returns from remote sensing investments. The outcomes of this research are expected to broadly impact next-generation wireless networks and Internet of Things applications with high traffic demands, such as autonomous driving, smart cities and remote sensing.The goal of this project is to develop an intelligent dynamic spectrum access framework with unprecedented spectrum utilization efficiency and agility to support spectrum coexistence. The developed IDEA network platform supports heterogeneous devices from both primary and secondary active radios as well as passive radios. Key technical innovations are developed across the network to substantially enhance system-level spectrum utilization and active-passive radio coexistence. Specifically, analog/mixed-signal spiking neural network (SNN)-based neuromorphic computing hardware is designed to provide on-board intelligence at ultra-low power for resource-constrained secondary active radios. Model-free deep reinforcement learning is integrated with wireless domain knowledge and the SNN platform to accelerate learning-based spectrum access and coexistence. Advanced spectrum monitoring techniques are developed to quickly detect and characterize various signal emitters in both active and passive services. Finally, software and hardware testbeds are developed for system level evaluation and tradeoff optimization. The IDEA framework not only empowers efficient spectrum access in highly dynamic wireless environments, but also facilitates holistic system design and optimization across devices and circuits, sensing and communications, and networking.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.