CIF: Small: Ubiquitous RF Sensing with Smart Metasurfaces
CIF: Small: Ubiquitous RF Sensing with Smart Metasurfaces
批准号:
2316865
负责人:
Hongbin Li
金额:
$60.0万
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
项目状态:
未结题
起止时间:
2023-08-01 至 2026-07-31
中文摘要
由于无线通信的普及,射频(RF)传感正变得越来越普遍。值得注意的是,即将推出的WiFi标准IEEE802.11bf将使无线设备能够像雷达一样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四周并定位非视线目标。为了解决这个问题,通常采用的方法包括在监视区域部署多个RF发射器和接收器,以便至少有一个发射器-接收器对可以观察到目标。不幸的是,这种分布式射频传感系统体积庞大,成本高昂,操作负担沉重,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可替代的分布式射频传感范例,该范例可以通过利用可重构智能表面(RIS)有效地“观察”周围的角落,RIS是一种薄平面结构,由许多小型低成本超材料元件组成,可以独立调整以控制入射射频信号的反射。与墙纸一样,RIS可以覆盖建筑物、墙壁和天花板的部分区域,使射频工程师能够根据特定需求主动定制无线电环境。这项工作将推进RIS辅助射频传感的基础理论和实践方法。该项目的研究成果将有可能与未来的无线网络相结合,使服务提供商能够为其客户提供智能射频传感和通信服务。该项目的目标是建立一个系统的信号处理框架,用于在分布式环境中由RIS辅助的无处不在的射频传感。在这些设置中,发射器和接收器可以位于同一位置或空间分布,部署RISs以协助目标照明和/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进行联合优化,也包括被动传感,它利用环境无线源,如蜂窝和WiFi信号,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,考虑分布式传感系统固有的多路径和异步传播。Thrust 2开发了训练有效的信道估计技术,包括估计连续连接发射机、RIS、目标和接收器的级联信道的方法,以及估计级联信道统计的方法。最后,Thrust 3探索了使用多层结构的RIS进行射频传感,提供了额外的射频信号处理能力,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。
英文摘要
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.
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DOI:
10.1109/radarconf2351548.2023.10149772
发表时间:
2023-05
期刊:
2023 IEEE Radar Conference (RadarConf23)
影响因子:
--
作者:
[Fangzhou Wang;A. L. Swindlehurst;Hongbin Li]
通讯作者:
Fangzhou Wang;A. L. Swindlehurst;Hongbin Li
DOI:
10.1109/radarconf2351548.2023.10149555
发表时间:
2023-05
期刊:
2023 IEEE Radar Conference (RadarConf23)
影响因子:
--
作者:
[Cengcang Zeng;Fangzhou Wang;Hongbin Li;Mark A. Govoni]
通讯作者:
Cengcang Zeng;Fangzhou Wang;Hongbin Li;Mark A. Govoni
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]
通讯作者:
Bin Wang;Jun Fang;Hongbin Li;Xiaojun Yuan;Qing Ling
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]
通讯作者:
Hanyu Wang;Jun Fang;Hongbin Li
DOI:
10.1109/radarconf2351548.2023.10149583
发表时间:
2023-05
期刊:
2023 IEEE Radar Conference (RadarConf23)
影响因子:
--
作者:
[Fangzhou Wang;Hongbin Li;A. L. Swindlehurst]
通讯作者:
Fangzhou Wang;Hongbin Li;A. L. Swindlehurst
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