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使用软件无线电技术实现实时多频带频谱感知。

Real-Time Implementation of Multiband Spectrum Sensing Using SDR Technology.

机构信息

Electrical Engineering Department, Metropolitan Autonomous University Iztapalapa, Mexico City 09360, Mexico.

出版信息

Sensors (Basel). 2021 May 18;21(10):3506. doi: 10.3390/s21103506.

DOI:10.3390/s21103506
PMID:34069877
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8157380/
Abstract

In this work, a novel multiband spectrum sensing technique is implemented in the context of cognitive radios. This technique is based on multiresolution analysis (wavelets), machine learning, and the Higuchi fractal dimension. The theoretical contribution was developed before by the authors; however, it has never been tested in a real-time scenario. Hence, in this work, it is proposed to link several affordable software-defined radios to sense a wide band of the radioelectric spectrum using this technique. Furthermore, in this real-time implementation, the following are proposed: (i) a module for the elimination of impulsive noise, with which the appearance of sudden changes in the signal is reduced through the detail coefficients of the multiresolution analysis, and (ii) the management of different devices through an application that updates the information of each secondary user every 100 ms. The performance of these linked devices was evaluated with encouraging results: 95% probability of success for signal-to-noise ratio (SNR) values greater than 0 dB and just five samples (mean) in error of the edge detection (start and end) for a primary user transmission.

摘要

在这项工作中，一种新的多频带频谱感知技术在认知无线电的背景下实现。该技术基于多分辨率分析（小波）、机器学习和 Higuchi 分形维数。该理论贡献是由作者之前提出的；然而，它从未在实时场景中进行过测试。因此，在这项工作中，建议使用这种技术将几个负担得起的软件定义无线电连接起来，以感知无线电频谱的宽频带。此外，在这个实时实现中，提出了以下两个方面：（i）一个用于消除脉冲噪声的模块，通过多分辨率分析的细节系数，减少信号的突然变化，（ii）通过一个每 100ms 更新每个次用户信息的应用程序来管理不同的设备。这些连接设备的性能评估结果令人鼓舞：对于信噪比（SNR）值大于 0dB 的信号，成功的概率为 95%，而对于主用户传输的边缘检测（开始和结束），平均只有 5 个样本的误差。

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