基于对数累积量的重尾分布脉冲干扰参数估计及性能分析

Parameter estimator based on the log-cumulant and its performance analysis for heavy-tailed-distributed impulsive interference

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.

The impulsive interference in many wireless communication networks can be modeled as a symmetricα-stable distribution noise. The probability density function of the interference needs to be obtained in advance in signal detection, channel decoding, wireless network outage probability, and bit error rate analysis application scenarios. The method of log-cumulant is used to estimate the characteristic exponent and dispersion of the interference. Furthermore, the probability distribution of the estimated parameters is derived in detail, which can be used for quantitative analysis to evaluate the estimation reliability. In addition, the noise in the receiver of the actual system is bivariate mixture noise including the independent Gaussian noise and SαS interference. We suggest that the bivariate noise can be approximated from its univariate counterpart. We prove that this type of approximation is reasonable by means of simulation and numerical calculation. The relationship between the parameters of the mixture noise and the geometric power signal-to-noise ratio are provided in this paper based on this assumption. The estimator based on the log-cumulant and performance analysis is therefore still valid in the bivariate noise environment.