A software-defined sensor architecture for large-scale wideband spectrum monitoring

Damian Pfammatter, D. Giustiniano, Vincent Lenders
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引用次数: 56

Abstract

Today's spectrum measurements are mainly performed by governmental agencies which drive around using expensive specialized hardware. The idea of crowdsourcing spectrum monitoring has recently gained attention as an alternative way to capture the usage of wide portions of the wireless spectrum at larger geographical and time scales. To support this vision, we develop a flexible software-defined sensor architecture that enables distributed data collection in real-time over the Internet. Our sensor design builds upon low-cost commercial off-the-shelf (COTS) hardware components with a total cost per sensor device below $100. The low-cost nature of our sensor platform makes the sensing approach particularly suitable for large-scale deployments but imposes technical challenges regarding performance and quality. To circumvent the limits of our solution, we have implemented and evaluated different sensing strategies and noise reduction techniques. Our results suggest that our sensor architecture may be useful in application areas such as dynamic spectrum access in cognitive radios, detecting regions with elevated electro-smog, or simply to gain an understanding of the spectrum usage for advanced signal intelligence such as anomaly detection or policy enforcement.
一种用于大规模宽带频谱监测的软件定义传感器架构
今天的频谱测量主要是由政府机构进行的,他们使用昂贵的专业硬件。众包频谱监测的想法最近引起了人们的注意,因为它是在更大的地理和时间尺度上捕捉大部分无线频谱使用情况的一种替代方法。为了支持这一愿景,我们开发了一种灵活的软件定义传感器架构,可以通过互联网实时收集分布式数据。我们的传感器设计基于低成本的商用现货(COTS)硬件组件,每个传感器设备的总成本低于100美元。我们传感器平台的低成本特性使得传感方法特别适合大规模部署,但在性能和质量方面带来了技术挑战。为了规避我们的解决方案的局限性,我们已经实施和评估了不同的传感策略和降噪技术。我们的研究结果表明,我们的传感器架构可能在认知无线电中的动态频谱接入、检测电烟雾升高的区域等应用领域有用,或者只是为了了解高级信号智能(如异常检测或政策执行)的频谱使用情况。
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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