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.

由于无线通信的激增，射频（RF）感测变得越来越普遍。值得注意的是，即将推出的WiFi标准IEEE802.11bf将使无线设备能够充当雷达，以感知周围环境并确定附近物体的位置。然而，大多数射频传感器无法环顾角落并定位非视线目标。为了解决这个问题，通常采用的方法涉及在监视区域内部署多个RF发射器和接收器，使得目标可以由至少一个发射器-接收器对观察到。不幸的是，这种分布式RF感测系统体积庞大、成本高、操作繁琐，并且由于过度辐射而对环境不友好。为了克服这些缺点，该项目旨在开发一种替代的分布式RF感测范例，该范例可以通过利用可重构智能表面（RIS）来有效地“看”周围的角落，该智能表面是一种薄的平面结构，包括许多小的低成本超材料元件，可以独立地调整以控制入射RF信号的反射。与墙纸一样，RIS可以覆盖建筑物、墙壁和天花板的部分，使RF工程师能够根据特定需求主动定制无线电环境。本文的工作将为RIS辅助射频传感的基础理论和实用方法的发展提供参考。该项目的研究成果将有可能与未来的无线网络集成，使服务提供商能够为客户提供智能RF传感和通信服务。 本项目的目标是建立一个系统化的信号处理框架，用于分布式环境中RIS辅助的无处不在的RF传感。在这些设置中，发射器和接收器可以位于同一地点或空间分布，其中部署RIS以辅助目标照明和/或观察。所提出的框架既包括主动传感，其中专用发射器作为系统的一部分被联合优化，也包括被动传感，其采用诸如蜂窝和WiFi信号的环境无线源来探测环境。研究工作分为三个重点。推力1侧重于系统设计和优化，考虑到分布式传感系统中固有的多径和异步传播。推力2开发训练有效的信道估计技术，包括方法来估计级联信道，串行连接发射机，RIS，目标，和接收机，以及方法估计级联信道的统计。最后，Thrust 3探索了使用具有多层结构的RIS进行RF传感，该结构提供了额外的RF信号处理能力，同时降低了硬件复杂性和能耗。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。

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

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

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

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