SWIFT: LARGE: Averting Wireless Spectrum Pollution in the Era of Low-Power IoT

SWIFT：大型：避免低功耗物联网时代的无线频谱污染

• 批准号: 2030154
• 负责人: Swarun Kumar
• 金额: $ 100万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2030154&HistoricalAwards=false
• 关键词: SWIFT; LARGE; Averting; Wireless; Spectrum

This project seeks to address the problem of spectrum pollution in the Internet-of-Things (IoT) era. Spectrum pollution is an inevitable challenge that emerges when low-cost and low-power wireless IoT devices deployed at scale cannot detect and respect the presence of other devices on shared spectrum. The core challenge is the low-power and simplicity of most IoT devices, due to which they are narrowband and unable to sense and avoid incumbents on shared spectrum. The project investigates a system that allows teams of geo-distributed low-power devices to quickly and efficiently scan wide bandwidths to avert interference. This proposal presents Swallow, a system design for low-power devices to sense spectrum at minimal energy and cost, allowing these devices to behave as low-cost and distributed spectrum observatories. The testbed developed through the project will serve as a vehicle for undergraduate and graduate-level projects as well as workshops for K-12 students in the City of Pittsburgh. The team has direct experience working with sensor deployments both at Carnegie Mellon, the City of Pittsburgh, United States Geological Survey (USGS), and local industry partners and will leverage these connections to deploy Swallow at scale.The project will study a low-power analog frontend and associated digital processing that allows IoT devices to summarize large bandwidths using inexpensive components. It investigates an end-to-end system design that collates measurements from distributed individually low-power IoT devices to obtain a shared spectrum map. It further develops an accurate localization framework to geo-locate individual IoT devices to sample spectrum occupancy at fine-spatial resolution. The wide bandwidth of Swallow’s low-power frontend naturally leads to an accurate solution for time-of flight based localization, where bandwidth is a key metric that dictates system accuracy. Swallow proposes a sub-meter accurate ranging solution for low-power wide-area radios that enables detecting proximity to known passive RF devices such as fixed radio telescopes and enables spectrum occupancy maps sampled at fine-spatial resolution. The project will be implemented and evaluated on a large programmable Low-Power Wide-Area Networking testbed in the Carnegie Mellon University campus that serves large parts of the City of Pittsburgh.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.

该项目旨在解决物联网 (IoT) 时代的频谱污染问题。当大规模部署的低成本、低功耗无线物联网设备无法检测和尊重其存在时，频谱污染是不可避免的挑战。核心挑战是大多数物联网设备的低功耗和简单性，因此它们是窄带的，无法感知和避开共享频谱上的现有设备。分布式低功耗设备可以快速该提案提出了 Swallow，这是一种用于低功耗设备的系统设计，能够以最低的能量和成本感测频谱，使这些设备能够充当低成本和分布式频谱观测站。该项目将作为匹兹堡市本科和研究生水平项目以及 K-12 学生研讨会的载体。该团队在美国匹兹堡市卡内基梅隆大学地质学院拥有直接的传感器部署经验。民意调查（美国地质调查局）和当地行业合作伙伴，并将利用这些连接大规模部署 Swallow。该项目将研究低功耗模拟前端和相关数字处理，使物联网设备能够使用廉价组件汇总大带宽。它进一步开发了一个精确的定位框架，以对各个物联网设备进行地理定位，以精细的空间分辨率对宽带宽的频谱占用进行采样。的Swallow 的低功耗前端自然会带来基于飞行时间的定位的精确解决方案，其中带宽是决定系统精度的关键指标，Swallow 为低功耗广域无线电提出了亚米级精确测距解决方案，可实现检测。接近已知的无源射频设备，例如固定射电望远镜，并能够以精细空间分辨率采样频谱占用图。该项目将在大型可编程低功耗广域网上实施和评估。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力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

Battery-free Wideband Spectrum Mapping using Commodity RFID Tags

使用商品 RFID 标签进行无电池宽带频谱映射

• DOI: 10.1145/3570361.3592508
• 发表时间: 2023-07-10
• 期刊: Proceedings of the 29th Annual International Conference on Mobile Computing and Networking
• 作者: Mohamed Ibrahim Ahmed;A. Bansal;Kuang Yuan;Swarun Kumar;P. Steenkiste
• 通讯作者: P. Steenkiste

TagFi: Locating Ultra-Low Power WiFi Tags Using Unmodified WiFi Infrastructure

TagFi：使用未经修改的 WiFi 基础设施定位超低功耗 WiFi 标签

• DOI: 10.1145/3448082
• 发表时间: 2021-10
• 期刊: UbiComp
• 作者: Elahe Soltanaghaei; Adwait Dongare
• 通讯作者: Adwait Dongare

OwLL: Accurate LoRa Localization using the TV Whitespaces

OwLL：使用电视空白进行准确的 LoRa 定位

• DOI: 10.1145/3412382.3458263
• 发表时间: 2021-05-18
• 期刊: Proceedings of the 20th International Conference on Information Processing in Sensor Networks (co-located with CPS-IoT Week 2021)
• 作者: A. Bansal;Akshay Gadre;Vaibhav Singh;Anthony G. Rowe;Bob Iannucci;Swarun Kumar
• 通讯作者: Swarun Kumar

Cross Technology Distributed MIMO for Low Power IoT

适用于低功耗物联网的跨技术分布式 MIMO

• DOI: 10.1109/tmc.2020.3029218
• 发表时间: 2020-01
• 期刊: IEEE Transactions on Mobile Computing
• 影响因子: 7.9
• 作者: Narayanan, Revathy;Kumar, Swarun;Murthy, Siva Ram
• 通讯作者: Murthy, Siva Ram