RINGS: Resilient mmWave Networks via Distributed In-Surface Computing (mmRISC)

无线网络正在经历一场彻底的变革，其目标是为21世纪提供关键的信息基础设施，并促进新的经济机遇、创新和许多新兴应用。为了促进这一点，人们关注毫米波频率范围内的新频谱，这些频谱能够支持自动化、机器人和网络物理系统、智能健康以及自动驾驶汽车和系统中应用所需的超高数据速率和低延迟。该频谱还可以支持无线回程链路，以桥接最后一英里连接，并提供宽带无线接入-其重要性在新冠肺炎大流行期间得到了明确强调。 然而，这些连接链路易于发生物理信道中断，包括阻塞和信道传播变化，因此没有弹性。该提案涉及三个不同研究小组的多学科方法，以解决这些问题并确保此类网络的弹性和可扩展性。所提出的智能反射表面的概念旨在实现无线信道的动态和按需控制，以创建有利的传输，从而允许在移动的毫米波WLAN中的鲁棒无线连接。该项目的成功可以实现下一代、无处不在和低成本的毫米波无线接入，包括灵活部署无线回程，解决最后一英里连接、卫星通信和智能城市和网络物理系统的智能无线传感系统。该项目将通过在严格的多学科研究工作中对本科和博士课程的学生进行培训，满足发展以美国为中心的半导体和无线技术能力的需求。这个项目，mmRISC，通过分布式表面计算构建弹性毫米波网络。 我们研究毫米波，多波段混合表面与嵌入式定制硅IC，提供表面上的信号放大和多用户定位，跟踪和环境传感的计算能力。 我们提出的表面使弹性和可重构的分布式网络，保持低延迟，能源和频谱效率。我们追求一种全面的跨系统研究方法，专注于可扩展的，频谱灵活的，低功耗和低成本的混合表面，可在多个毫米波频段上操作，并具有受控放大。我们还将专注于用于表面传感的嵌入式计算，以及支持此类智能表面的弹性网络架构，从而实现容量优化。通过跨层设计方法，我们提出的工作将为未来NextG表面辅助无线网络的架构提供信息。该奖项反映了NSF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。

Wireless networks are undergoing a radical transformation with the aim to provide the critical information infrastructure for the 21st century and foster new economic opportunities, innovation and many emerging applications. To facilitate this, there is a focus on new spectrum in the millimeter-wave frequency range that has the ability to support ultra-high data rates with low latency needed for applications in automation, robotics and cyber-physical systems, smart health, and autonomous vehicles and systems. The spectrum can also support wireless backhaul links to bridge the last mile connectivity, and provide broadband wireless access---the importance of which is clearly highlighted during the Covid-19 pandemic. However, these connectivity links are prone to physical channel disruptions including blockages and channel propagation variations, and therefore not resilient. The proposal involves a multi-disciplinary approach across three different research groups towards addressing these problems and ensuring resilience and scalability in such networks. The proposed concept of smart reflecting surfaces aims to enable dynamic and on-demand control of wireless channels to create favorable transmission allowing robust wireless connectivity in mobile mmWave WLANs. The success of this project can enable the next-generation, ubiquitous, and low-cost mmWave wireless access, including flexible deployment of wireless backhauls addressing the last-mile connectivity, satellite communication, and intelligent wireless sensing systems for smart cities and cyber-physical systems. The project will address the need for developing US-centric capabilities in semiconductors and wireless technology, through training of students across the undergraduate and the PhD program in a rigorous multi-disciplinary research effort. This project, mmRISC, builds Resilient mmWave Networks via Distributed In-Surface Computing. We investigate mmWave, multi-band hybrid surfaces with embedded custom-silicon ICs that provide on-surface signal amplification and computing abilities for multi-user localization, tracking and ambient sensing. Our proposed surfaces enable resilient and reconfigurable distributed networks that maintain low latency, energy and spectral efficiency. We pursue a holistic, cross-system research approach focusing on scalable, spectrally-agile, low-power, and low-cost hybrid surfaces operable across multiple mmWave bands with controlled amplification. We will also focus on embedded computing for on-surface sensing, and resilient network architectures supporting such smart surfaces allowing capacity optimization. Through cross-layer design approaches, our proposed work will inform the architecture of NextG surface-assisted wireless networks for the future.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.