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

RINGS：通过分布式表面计算 (mmRISC) 的弹性毫米波网络

• 批准号: 2148271
• 负责人: Kaushik Sengupta
• 金额: $ 100万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2148271&HistoricalAwards=false
• 关键词: RINGS; Resilient; mmWave; Networks; via

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.

无线网络正在进行根本性的转变，目的是为21世纪提供关键的信息基础设施，并促进新的经济机会，创新和许多新兴应用。为了促进这一点，关注毫米波频率范围的新频谱，该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自动驾驶汽车和系统所需的低潜伏期超高数据速率。该频谱还可以支持无线回程链接，以桥接最后一英里的连接，并提供宽带无线访问 - - 在Covid-19大流行期间，其重要性显然突出了。 但是，这些连通性链接容易遭受物理通道中断，包括阻塞和通道传播变化，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中的韧性和可伸缩性。提出的智能反射表面的概念旨在使无线通道的动态和按需控制能够创建有利的传输，从而在移动MMWave WLAN中允许稳健的无线连接。该项目的成功可以使下一代，无处不在和低成本的MMWave无线访问，包括灵活地部署无线次数，以解决最后一英里的连接，卫星通信以及针对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学生和博士学位课程进行培训，以在半导体和无线技术中开发以美国为中心的能力。该项目MMRISC通过分布式的表面计算构建了弹性的MMWave网络。 我们研究了具有嵌入式自定义 - 硅胶IC的MMWave，多波段混合表面，可为多用户定位，跟踪和环境传感提供表面信号放大和计算能力。 我们提出的表面可实现保持低潜伏期，能量和光谱效率的弹性和可重构分布式网络。我们采用一种整体，跨系统研究方法，重点是可扩展的，弹性，低功率和低成本混合表面，可在具有控制放大的多个MMWAVE频段上操作。我们还将专注于用于地下传感的嵌入式计算，以及支持此类智能表面的弹性网络体系结构，允许容量优化。通过跨层设计方法，我们拟议的工作将为NextG表面辅助无线网络的架构提供未来的架构。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的评估评估标准来通过评估来获得支持的。

项目成果

Towards dual-band reconfigurable metasurfaces for satellite networking

• DOI: 10.1145/3563766.3564086
• 发表时间: 2022-11
• 期刊: Proceedings of the 21st ACM Workshop on Hot Topics in Networks
• 作者: Kun Woo Cho;Yasaman Ghasempour;K. Jamieson

Wavefront Manipulation Attack via Programmable mmWave Metasurfaces: from Theory to Experiments

• DOI: 10.1145/3558482.3590182
• 发表时间: 2023-05
• 期刊: Proceedings of the 16th ACM Conference on Security and Privacy in Wireless and Mobile Networks
• 作者: Haoze Chen;H. Saeidi;S. Venkatesh;K. Sengupta;Yasaman Ghasempour

A Low-Power OAM Metasurface for Rank-Deficient Wireless Environments

• DOI: 10.1109/globecom54140.2023.10436974
• 发表时间: 2023-12
• 期刊: GLOBECOM 2023 - 2023 IEEE Global Communications Conference
• 作者: Kun Woo Cho;Srikar Kasi;Kyle Jamieson

LeakyScatter: A Frequency-Agile Directional Backscatter Network Above 100 GHz

• 发表时间: 2023
• 作者: Atsu Kludze;Yasaman Ghasempour

Towards Terahertz Wireless Authentication with Unique Aperture Fingerprints using Leaky-Wave Antennas

使用漏波天线通过独特的孔径指纹实现太赫兹无线身份验证

• 发表时间: 2022
• 期刊: Millimeter and Terahertz Waves (IRMMW-THz
• 作者: Atsutse Kludze;Yasaman Ghasempour
• 通讯作者: Yasaman Ghasempour