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A Novel Multiband Spectrum Sensing Method Based on Wavelets and the Higuchi Fractal Dimension

机译:基于小波和Hi口分形维数的多频带频谱感知新方法

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摘要

In this work, two novel methodologies for the multiband spectrum sensing in cognitive radios are implemented. Methods are based on the continuous wavelet transform (CWT) and the multiresolution analysis (MRA) to detect the edges of available holes in the considered wideband spectrum. Besides, MRA is also combined with the Higuchi fractal dimension (a non-linear measure) to establish the decision rule permitting the detection of the absence or presence of one or multiple primary users in the studied wideband spectrum. Methods were tested on simulated and real signals showing a good performance. The results present these two methods as effective options for detecting primary user activity on the multiband spectrum. The first methodology works for 95% of cases, while the second one presents 98% of effectivity under simulated signals of signal-to-noise ratios (SNR) higher than 0 dB.
机译:在这项工作中,实现了两种用于认知无线电中的多频带频谱感测的新颖方法。方法基于连续小波变换(CWT)和多分辨率分析(MRA)来检测所考虑的宽带频谱中可用孔的边缘。此外,MRA还与Higuchi分形维数(一种非线性度量)相结合,建立了决策规则,允许检测所研究的宽带频谱中是否存在一个或多个主要用户。方法对模拟和真实信号进行了测试,显示出良好的性能。结果表明这两种方法是检测多频带频谱上主要用户活动的有效选择。第一种方法适用于95%的情况,而第二种方法在信噪比(SNR)高于0 dB的模拟信号下具有98%的有效性。

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