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。频谱污染是一个不可避免的挑战，当大规模部署的低成本和低功耗无线物联网设备无法检测和尊重共享频谱上其他设备的存在时，就会出现这种情况。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任者。该项目研究了一种系统，该系统允许地理分布的低功耗设备团队快速有效地扫描宽带以避免干扰。该提案提出了Swallow，这是一种低功耗设备的系统设计，可以以最小的能量和成本感测频谱，使这些设备能够作为低成本和分布式频谱观测站。通过该项目开发的测试平台将作为本科生和研究生项目的工具，以及匹兹堡市K-12学生的研讨会。该团队拥有在卡内基梅隆大学、匹兹堡市、美国地质调查局（USGS）和当地行业合作伙伴部署传感器的直接经验，并将利用这些联系大规模部署Swallow。该项目将研究低功耗模拟前端和相关的数字处理，使物联网设备能够使用廉价的组件总结大带宽。它研究了一种端到端系统设计，该设计整理来自分布式低功耗物联网设备的测量结果，以获得共享的频谱图。它进一步开发了一个精确的定位框架，以地理定位单个物联网设备，从而以精细的空间分辨率对频谱占用进行采样。Swallow的低功耗前端的宽带宽自然会为基于飞行时间的定位提供准确的解决方案，其中带宽是决定系统精度的关键指标。Swallow提出了一种用于低功率广域无线电的亚米级精确测距解决方案，该解决方案能够检测与固定射电望远镜等已知无源RF设备的接近程度，并能够以精细的空间分辨率采样频谱占用图。该项目将在卡内基梅隆大学校园内的一个大型可编程低功耗广域网测试平台上实施和评估，该平台为匹兹堡市的大部分地区提供服务。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

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
• 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

Battery-free Wideband Spectrum Mapping using Commodity RFID Tags

• DOI: 10.1145/3570361.3592508
• 发表时间: 2023-07
• 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