论文标题

两个措施是两个措施:软件无线电平台的无校准完整双工监视

Two Measure is Two Know: Calibration-free Full Duplex Monitoring for Software Radio Platforms

论文作者

Wang, Jie, Gornet, Jonathan, Orange, Alex, Stoller, Leigh, Wong, Gary, Van Der Merwe, Jacobus, Kasera, Sneha Kumar, Patwari, Neal

论文摘要

未来的虚拟化无线电访问网络(VRAN)基础架构提供商(以及当今的实验性无线测试床提供商)可能同时不确定其基站正在传输哪些信号,并对违规行为合法责任。这些提供商必须监视传输和外部信号的范围,而无需访问无线电本身。在本文中,我们提出了FDMonitor,这是一个连接发射器及其天线之间的全双工监测系统,以实现此目标。在RF路径上测量这一点的信号是必要的,但由于天线是双向装置,因此不足。因此,FDMonitor使用双向耦合器,两通道接收器和新的源分离算法同时估计发射的信号和入射在天线上的信号。我们还可以自适应地估计系统的线性模型,而不是需要离线校准。 FDMonitor一直在现实世界中的开放无线测试床上运行,监视了外部实验人员在七个月内控制的19个SDR平台(带有裸机访问),每当观察到违规时,都会发出警报。我们的实验结果表明,FDMonitor准确地分离了一系列信号参数的信号。在超过7个月的观察中,它的正预测值为97%,共有20个错误的警报。

Future virtualized radio access network (vRAN) infrastructure providers (and today's experimental wireless testbed providers) may be simultaneously uncertain what signals are being transmitted by their base stations and legally responsible for their violations. These providers must monitor the spectrum of transmissions and external signals without access to the radio itself. In this paper, we propose FDMonitor, a full-duplex monitoring system attached between a transmitter and its antenna to achieve this goal. Measuring the signal at this point on the RF path is necessary but insufficient since the antenna is a bidirectional device. FDMonitor thus uses a bidirectional coupler, a two-channel receiver, and a new source separation algorithm to simultaneously estimate the transmitted signal and the signal incident on the antenna. Rather than requiring an offline calibration, we also adaptively estimate the linear model for the system on the fly. FDMonitor has been running on a real-world open wireless testbed, monitoring 19 SDR platforms controlled (with bare metal access) by outside experimenters over a seven month period, sending alerts whenever a violation is observed. Our experimental results show that FDMonitor accurately separates signals across a range of signal parameters. Over more than 7 months of observation, it achieves a positive predictive value of 97%, with a total of 20 false alerts.

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