Synchrosqueezing Transform Based Methodology for Radiometric Identification

G. Baldini, G. Steri, Raimondo Giuliani
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引用次数: 1

Abstract

This paper describes the application of the SynchroSqueezing Transform (SST) to the problem of radiometric identification, which means that wireless devices can be identified and authenticated through their radio frequency emissions. Radiometric identification has been applied to enhance the security of wireless networks based on WiFi or cellular communication standards. In literature, radiometric identification has been performed by feature extraction in the 1D time domain, 1D frequency domain or also in the 2D time-frequency domain. This paper describes the novel application of the 2D SST to the problem of radiometric identification. An experimental data set of Radio Frequency (RF) emissions from 12 wireless devices is used to evaluate the performance of the SST transform in terms of identification accuracy. This paper shows that the identification accuracy obtained using 2D SST is superior to conventional techniques based in the 1D time domain or 1D frequency domain especially in presence of gaussian noise. 1 This work has been partially supported by the European Commission through project SerIoT funded by the European Union H2020 Programme under Grant Agreement No. 780139. The opinions expressed in this paper are those of the authors and do not necessarily reflect the views of the European Commission.
基于同步压缩变换的辐射识别方法
本文描述了同步压缩变换(SST)在辐射识别问题中的应用,这意味着无线设备可以通过其射频发射来识别和认证。辐射识别已被应用于增强基于WiFi或蜂窝通信标准的无线网络的安全性。在文献中,辐射识别已经通过一维时域、一维频域或二维时频域的特征提取来完成。本文介绍了二维海表温度在辐射识别问题中的新应用。利用来自12个无线设备的射频(RF)发射实验数据集来评估海温变换在识别精度方面的性能。结果表明,在存在高斯噪声的情况下,二维海表温度的识别精度优于基于一维时域或一维频域的常规方法。这项工作得到了欧盟委员会的部分支持,由欧盟H2020计划资助的SerIoT项目,资助协议号为780139。本文中表达的观点是作者的观点,并不一定反映欧盟委员会的观点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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