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Sums of lognormal random variables (RVs) occur in many important problems inwireless communications especially in interferences calculation. Severalmethods have been proposed to approximate the lognormal sum distribution. Mostof them requires lengthy Monte Carlo simulations, or advanced slowly convergingnumerical integrations for curve fitting and parameters estimation. Recently,it has been shown that the log skew normal distribution can offer a tightapproximation to the lognormal sum distributed RVs. We propose a simple andaccurate method for fitting the log skew normal distribution to lognormal sumdistribution. We use moments and tails slope matching technique to find optimallog skew normal distribution parameters. We compare our method with those inliterature in terms of complexity and accuracy. We conclude that our method hassame accuracy than other methods but more simple. To further validate ourapproach, we provide an example for outage probability calculation in lognormalshadowing environment based on log skew normal approximation.

Fitting the Log Skew Normal to the Sum of Independent Lognormals Distribution