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Arbitrarily tight bounds on cumulative distribution function of Beckmann distribution

机译:Beckmann分布的累积分布函数的任意紧界

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Beckmann distribution is a versatile mathematical model, which can be applied in performance analyses of radio frequency communications, free-space optical communications and underwater optical communications. However, the cumulative distribution function (CDF) of Beckmann distribution does not have a closed-form expression, which makes it challenging to derive closed-form outage probability expression of communications over channels involving Beckmann random variables. In this paper, we derive closed-form upper and lower CDF bounds of Beckmann distribution, and the bounds can be arbitrarily tight by properly choosing the parameters of the bounds. Compared to the numerical estimation of the double-fold integral expression of the Beckmann CDF, using the closed-form bounds to estimate the CDF is not only faster, but also has less space complexity. More importantly, the analytical CDF bounds explicitly quantify the largest possible discrepancy between the approximate CDF and the exact CDF, while the discrepancy of the numerical estimation is unknown.
机译:贝克曼分布是一种通用的数学模型,可用于射频通信,自由空间光通信和水下光通信的性能分析。但是,贝克曼分布的累积分布函数(CDF)不具有封闭形式的表达式,这使得在涉及贝克曼随机变量的信道上导出通信的封闭形式中断概率表达式具有挑战性。在本文中,我们推导出上部封闭形式的,并降低贝克曼分布的CDF界限,界限可以通过适当选择的边界的参数是任意紧。与贝克曼CDF的两倍积分表达式的数值估计相比,使用封闭形式的边界估计CDF不仅速度更快,而且空间复杂度更低。更重要的是,分析性CDF边界明确量化了近似CDF和精确CDF之间的最大可能差异,而数值估计的差异是未知的。

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