CIF: Small: Ubiquitous RF Sensing with Smart Metasurfaces

CIF：小型：采用智能超表面的无处不在的射频传感

• 批准号: 2316865
• 负责人: Hongbin Li
• 金额: $ 60万
• 依托单位: Stevens Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2316865&HistoricalAwards=false
• 关键词: CIF; Small; Ubiquitous; RF; Sensing

Radio frequency (RF) sensing is becoming increasingly pervasive due to the proliferation of wireless communications. Remarkably, the upcoming WiFi standard IEEE802.11bf will enable wireless devices to function as radars to sense the surroundings and determine the position of nearby objects. Most RF sensors, however, are unable to look around the corner and locate non-line-of-sight targets. To address this problem, a commonly employed approach involves deploying multiple RF transmitters and receivers across the surveillance area, so that the target can be observed by at least one transmitter-receiver pair. Unfortunately, such a distributed RF sensing system is bulky, costly, operationally burdensome, and environmentally unfriendly due to excessive radiation. To overcome these shortcomings, this project aims to develop an alternative distributed RF sensing paradigm that can effectively “look” around the corner by leveraging a reconfigurable intelligent surface (RIS), which is a thin planar structure comprising numerous small low-cost metamaterial elements that can be independently adjusted to control the reflection of incident RF signals. Like wallpaper, RIS can cover parts of buildings, walls, and ceilings, allowing RF engineers to proactively customize the radio environment based on specific needs. This work will advance fundamental theory and practical methods for RF sensing aided by RIS. Research outcomes of this project will have the potential to be integrated with future wireless networks, empowering service providers to offer intelligent RF sensing and communication services to their customers. The objective of this project is to establish a systematic signal processing framework for ubiquitous RF sensing aided by RIS in distributed environments. In these settings, the transmitter and receiver may be co-located or spatially distributed, with RISs deployed to assist in target illumination and/or observation. The proposed framework encompasses both active sensing, where a dedicated transmitter is jointly optimized as a part of the system, and passive sensing, which employs ambient wireless sources, such as cellular and WiFi signals, to probe the environment. The research efforts are structured into three thrusts. Thrust 1 focuses on system design and optimization, taking into account multipath and asynchronous propagation inherent in the distributed sensing system. Thrust 2 develops training-efficient channel estimation techniques, including methods to estimate the cascade channel that serially links the transmitter, RIS, targets, and receiver, as well as approaches for estimating the statistics of the cascade channel. Lastly, Thrust 3 explores RF sensing using RIS with a multi-layer structure, which provides additional RF signal processing capabilities, while simultaneously reducing hardware complexity and energy consumption.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.

由于无线通信的扩散，射频（RF）灵敏度变得越来越普遍。值得注意的是，即将到来的WiFi标准IEEE802.11BF将使无线设备充当雷达，以感知周围环境并确定近对象的位置。但是，大多数RF传感器都无法绕过拐角处并定位非视线目标。为了解决这个问题，一种常用的方法涉及在整个监视区域部署多个RF发射器和接收器，以便至少一个发射器接收器对可以观察到目标。不幸的是，由于过度的辐射，这种分布的RF灵敏度系统是庞大，昂贵的，在操作上易碎的且环境不友好的。为了克服这些缺点，该项目旨在开发一种替代分布式的RF敏感性范式，可以通过利用可重构的智能表面（RIS）来有效地“看”拐角处，该表面（RIS）是一种薄的平面结构，完成了许多可以独立调整以控制入射RF Signers RF Signers的反射。像墙纸一样，RIS可以涵盖建筑物，墙壁和天花板的一部分，从而使RF工程师可以根据特定需求主动自定义无线电环境。这项工作将推进RIS的基本理论和RF感知的实用方法。该项目的研究成果将有可能与未来的无线网络集成，从而授权服务提供商为客户提供智能的RF敏感性和通信服务。该项目的目的是为无处不在的RF灵敏度建立一个系统的信号处理框架，由RIS在分布式环境中提供帮助。在这些设置中，可以将发射器和接收器共同分配或空间分布，而RIS部署以协助目标照明和/或观察。所提出的框架增强了主动灵敏度，其中专用发射器被共同优化为系统的一部分，而被动敏感性则是雇员的环境无线源（例如蜂窝和WiFi信号）来探测环境。研究工作被构成三个推力。考虑到分布式传感系统固有的多径和异步传播，推力1专注于系统设计和优化。推力2开发了训练式通道估计技术，包括估算串联通道的方法，该通道连接发射器，RIS，目标和接收器，以及用于估计级联通道统计数据的方法。最后，推力3使用具有多层结构的RIS探索RF敏感性，该结构提供了其他RF信号处理能力，同时降低了硬件的复杂性和能源消耗。该奖项反映了NSF的法定任务，并通过使用该基金会的智力功能和广泛的影响来评估NSF的法定任务。

项目成果

Joint Antenna Selection and Transmit Beamforming for Dual-Function Radar-Communication Systems

• DOI: 10.1109/radarconf2351548.2023.10149772
• 发表时间: 2023-05
• 期刊: 2023 IEEE Radar Conference (RadarConf23)
• 作者: Fangzhou Wang;A. L. Swindlehurst;Hongbin Li

Bayesian Detection for Distributed MIMO Radar with Non-Orthogonal Waveforms in Non-Homogeneous Clutter

• DOI: 10.1109/radarconf2351548.2023.10149555
• 发表时间: 2023-05
• 期刊: 2023 IEEE Radar Conference (RadarConf23)
• 作者: Cengcang Zeng;Fangzhou Wang;Hongbin Li;Mark A. Govoni

Joint Beamforming and Channel Reconfiguration for RIS-Assisted Millimeter Wave Massive MIMO-OFDM Systems

• DOI: 10.1109/tvt.2023.3243389
• 发表时间: 2023-06
• 期刊: IEEE Transactions on Vehicular Technology
• 影响因子: 6.8
• 作者: Hanyu Wang;Jun Fang;Hongbin Li

Confederated Learning: Federated Learning With Decentralized Edge Servers

• DOI: 10.1109/tsp.2023.3241768
• 发表时间: 2022-05
• 期刊: IEEE Transactions on Signal Processing
• 影响因子: 5.4
• 作者: Bin Wang;Jun Fang;Hongbin Li;Xiaojun Yuan;Qing Ling

Clutter Suppression for Target Detection Using Hybrid Reconfigurable Intelligent Surfaces

• DOI: 10.1109/radarconf2351548.2023.10149583
• 发表时间: 2023-05
• 期刊: 2023 IEEE Radar Conference (RadarConf23)
• 作者: Fangzhou Wang;Hongbin Li;A. L. Swindlehurst