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Spread Spectrum Signal Detection in Overlay Systems using Maximum Entropy PDF Estimation Based on Fractional Moments

机译:基于分数阶矩的最大熵PDF估计的叠加系统扩频信号检测

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In this paper we introduce a new nonlinear detector to improve the performance of spread spectrum receiver in the presence of narrow-band interference. The new detector is blind in the sense that no training data is required. In our scheme we use maximum likelihood (ML) detection rule in conjunction with maximum entropy method (MEM) for probability density function (PDF) estimation of the observation noise. We use MEM with a new approach based on fractional moments instead of integer moments. The estimated PDF based on fractional moments is quite close to the true PDF. The results indicate that the new nonlinear detector outperforms conventional matched filter, and well known locally optimal (LO) detector
机译:在本文中,我们介绍了一种新型的非线性检测器,可在存在窄带干扰的情况下提高扩频接收机的性能。在不需要训练数据的意义上,新检测器是盲目的。在我们的方案中,我们将最大似然(ML)检测规则与最大熵方法(MEM)结合在一起用于观测噪声的概率密度函数(PDF)估计。我们将MEM与基于分数矩而不是整数矩的新方法结合使用。基于分数矩的估计PDF非常接近真实PDF。结果表明,新型非线性检测器的性能优于传统的匹配滤波器和众所周知的局部最优(LO)检测器

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