Collaborative Research: EARS: Crowd-based Spectrum Monitoring and Enforcement

合作研究：EARS：基于人群的频谱监控和执行

• 批准号: 1443956
• 负责人: Haitao Zheng
• 金额: $ 45.99万
• 依托单位: University of California-Santa Barbara
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2018-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1443956&HistoricalAwards=false
• 关键词: Collaborative; Research; EARS; Crowd; based

The scientists identify an important issue for a world of devices all communicating wirelessly: "How to identify malfunctioning devices or those not fairly sharing the spectrum with others?" The scientists explore scenarios for leveraging local, crowd-sourced mobile devices to detect and identify unauthorized transmitters. The goal of this technique is to reduce the cost of enforcement of network rules by adding the capability of some smart phones to sense the radio spectrum use and report back to a central database.The PIs propose to develop a Crowd-based Spectrum ENforcement System (CSENS), which takes a data-driven approach to spectrum enforcement. Specifically, the PIs propose to conduct 3 tasks: (i) real-time on-demand spectrum monitoring, which enables real-time responses to spectrum measurement tasks; (ii) utilizing physical layer features to embed cryptographic spectrum permits into transmissions, which enables reliably distinguish between authorized and unauthorized spectrum users; (iii) using a library of known signatures for network applications, unauthorized transmitters can be uniquely identified.

科学家们发现了一个无线通信设备世界的一个重要问题：“如何识别故障设备或那些不与其他设备公平共享频谱的设备？” 科学家们探索了利用本地众包移动设备来检测和识别未经授权的发射器的方案。 该技术的目标是通过增加一些智能手机的功能来感知无线电频谱使用并向中央数据库报告，从而降低网络规则的执行成本。 PI 建议开发一种基于人群的频谱执行系统（ CSENS），采用数据驱动的方法来实施频谱。具体而言，PI建议开展三项任务：（i）实时按需频谱监测，从而能够实时响应频谱测量任务； (ii) 利用物理层功能将加密频谱许可嵌入到传输中，从而能够可靠地区分授权和未经授权的频谱用户； (iii)使用网络应用的已知签名库，可以唯一地识别未经授权的发射机。