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

科学家们发现了一个重要的问题，为世界上的设备都无线通信：“如何识别故障设备或那些不公平地与他人共享频谱？“科学家们探索了利用本地众包移动的设备来检测和识别未经授权的发射机的方案。 这项技术的目标是通过增加一些智能手机的能力来感知无线电频谱的使用，并向中央数据库报告，以减少网络规则的执行成本。PI建议开发一个基于人群的频谱增强系统（CSENS），它采用数据驱动的方法来执行频谱。具体而言，PI建议执行3项任务：（i）实时按需频谱监控，从而实现对频谱测量任务的实时响应;（ii）利用物理层功能将加密频谱许可嵌入传输中，从而能够可靠地区分授权和未授权的频谱用户;（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。

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.