Albehadili Abdulsahib, Javaid Ahmad Y
Department of Electrical Engineering and Computer Science, The University of Toledo, Toledo, OH 43606, USA.
Department of Computer Engineering Technology, College of Information Technology, Imam Ja'afar Al-Sadiq University, Najaf 54001, Iraq.
Sensors (Basel). 2024 Aug 31;24(17):5670. doi: 10.3390/s24175670.
The authentication of wireless devices through physical layer attributes has attracted a fair amount of attention recently. Recent work in this area has examined various features extracted from the wireless signal to either identify a uniqueness in the channel between the transmitter-receiver pair or more robustly identify certain transmitter behaviors unique to certain devices originating from imperfect hardware manufacturing processes. In particular, the carrier frequency offset (CFO), induced due to the local oscillator mismatch between the transmitter and receiver pair, has exhibited good detection capabilities in stationary and low-mobility transmission scenarios. It is still unclear, however, how the CFO detection capability would hold up in more dynamic time-varying channels where there is a higher mobility. This paper experimentally demonstrates the identification accuracy of CFO for wireless devices in time-varying channels. To this end, a software-defined radio (SDR) testbed is deployed to collect CFO values in real environments, where real transmission and reception are conducted in a vehicular setup. The collected CFO values are used to train machine-learning (ML) classifiers to be used for device identification. While CFO exhibits good detection performance (97% accuracy) for low-mobility scenarios, it is found that higher mobility (35 miles/h) degrades (72% accuracy) the effectiveness of CFO in distinguishing between legitimate and non-legitimate transmitters. This is due to the impact of the time-varying channel on the quality of the exchanged pilot signals used for CFO detection at the receivers.
通过物理层属性对无线设备进行认证近来已引起了相当多的关注。该领域的近期工作研究了从无线信号中提取的各种特征，以识别发射机 - 接收机对之间信道的独特性，或者更稳健地识别源自不完善硬件制造过程的某些设备所特有的特定发射机行为。特别是，由于发射机和接收机对之间的本地振荡器失配而引起的载波频率偏移（CFO），在静止和低移动性传输场景中已表现出良好的检测能力。然而，在更高移动性的更动态时变信道中，CFO的检测能力如何仍不清楚。本文通过实验证明了时变信道中无线设备CFO的识别准确性。为此，部署了一个软件定义无线电（SDR）测试平台，以在实际环境中收集CFO值，其中在车辆设置中进行实际的发送和接收。收集到的CFO值用于训练机器学习（ML）分类器，以用于设备识别。虽然CFO在低移动性场景中表现出良好的检测性能（准确率97%），但发现更高的移动性（35英里/小时）会降低CFO在区分合法和非法发射机方面的有效性（准确率72%）。这是由于时变信道对接收机处用于CFO检测的交换导频信号质量的影响。
