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A pth order moment based spectrum sensing for cognitive radio in the presence of independent or weakly correlated Laplace noise

机译:在存在独立或弱相关的拉普拉斯噪声的情况下,基于p阶矩的认知无线电频谱感知

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摘要

In cognitive radio systems, noise samples are often assumed to be independent Gaussian in order to simplify the spectrum sensing problem. However, due to the high frequency of sampling, a certain level of correlation exists among the noise samples. Furthermore, non-Gaussian noise often has a negative effect on the signals which the secondary users finally receive. Spectrum sensing methods based on the independent Gaussian noise assumption may not achieve satisfying detection performance when noise samples are correlated and non-Gaussian distributed. A novel signal detection method based on pth order moments (POM) in a multi-user cooperative scheme is proposed to address spectrum sensing issue for both independent and weakly correlated Laplace noise. Different from other detectors, our detector does not require a priori knowledge of PU, noise and communication channels. Theoretical performance measures are derived and verified for both independent and weakly correlated Laplace noise. Moreover, the detection performances versus signal-to-noise ratio SNR, order p, scale parameter b and correlation coefficient τ of the background noise are investigated by computer simulation. It is shown that, for both independent and weakly correlated Laplace noises, the POM-based detector outperforms energy detector (ED) and polarity-coincidence-array (PCA) detector when p < 2.
机译:在认知无线电系统中,通常将噪声样本假定为独立的高斯,以简化频谱感测问题。但是,由于采样频率高,因此噪声样本之间存在一定程度的相关性。此外,非高斯噪声通常会对次级用户最终接收到的信号产生负面影响。当噪声样本相关且非高斯分布时,基于独立高斯噪声假设的频谱感测方法可能无法获得令人满意的检测性能。提出了一种在多用户协作方案中基于p阶矩(POM)的信号检测方法,以解决独立和弱相关拉普拉斯噪声的频谱感知问题。与其他探测器不同,我们的探测器不需要先验的PU,噪声和通信通道知识。推导并验证了独立和弱相关的拉普拉斯噪声的理论性能指标。此外,通过计算机仿真研究了检测性能与信噪比SNR,阶数p,比例参数b和背景噪声的相关系数τ的关系。结果表明,对于独立和弱相关的拉普拉斯噪声,当p <2时,基于POM的检测器的性能优于能量检测器(ED)和极性重合阵列(PCA)检测器。

著录项

  • 来源
    《Signal processing》 |2017年第8期|109-123|共15页
  • 作者单位

    College of Electronics and Information Engineering, Nanjing Tech University, Nanjing, 211816, China;

    College of Electronics and Information Engineering, Nanjing Tech University, Nanjing, 211816, China;

    College of Electronics and Information Engineering, Nanjing Tech University, Nanjing, 211816, China;

    Department of Electrical and Computer Engineering, Concordia University, Montreal, Quebec, H3G1M8, Canada;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Cognitive radio; Spectrum sensing; POM; Non-Gaussian noise;

    机译:认知广播;频谱感测;POM;非高斯噪声;

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