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在无线通信网络中存在用对称α稳定分布来建模的脉冲重尾干扰.而在信号检测、信道译码、无线网络中断概率及误码率分析等应用场景,需要预先知道干扰的概率密度函数.本文利用重尾干扰复信号包络的对数累积量,给出了特征指数和分散系数的估计算法,并具体推导出了参数估计变量的概率分布,该分布可用于定量分析估计的可靠性.除此之外,在实际系统中,接收端不仅有复对称α稳定分布描述的重尾脉冲干扰,还包括与之相互独立的复Gauss噪声,称之为双变量混合噪声.本文提出了用单变量的复对称α稳定分布模型来近似双变量混合噪声的方法.通过仿真和数值计算,验证了这种近似是合理的.再者,在此基础上,本文给出了混合噪声参数与几何功率信噪比之间的关系.因此,在合理的近似下,对数累积量的估计算法及性能分析在双变量混合噪声下仍然有效.
In wireless communication networks, there exists impulse heavy-tail interference modeled by symmetrical α-stable distribution, and in the application scenarios such as signal detection, channel decoding, wireless network interruption probability and bit error rate analysis, it is necessary to know the probability density function In this paper, we use the logarithm cumulant of heavy-tailed interfering signal envelope to give the estimation algorithm of characteristic index and dispersion coefficient, and deduce the probability distribution of parameter estimation variables, which can be used to quantitatively analyze the reliability of estimation In addition, in the real system, the receiver not only has the heavy-tail pulse interference described by the complex symmetric α-stable distribution, but also includes the independent complex Gauss noise which is called bivariate mixed noise. Single-variable complex symmetrical α-stable distribution model to approximate the bivariate mixed noise method.It is proved that this approximation is reasonable by simulation and numerical calculation.Furthermore, on this basis, the paper presents a hybrid noise parameter and geometry Power signal-to-noise ratio.Therefore, under a reasonable approximation, the estimation of logarithmic cumulants and the performance analysis are still valid under bivariate mixed noise.