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Comparison of methods of computing lognormal sum distributions and outages for digital wireless applications

机译:比较数字无线应用中对数正态和分布和中断的计算方法

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Four methods that can be used to approximate the distribution function (DF) of a sum of independent lognormal random variables (RVs) are investigated and compared. The aim is to determine the best method to compute the DF considering both accuracy and computational effort. The investigation focuses on values of the dB spread, /spl sigma/, valid for practical problems in wireless transmission (6 dB/spl les//spl sigma//spl les/12 dB). Similarly, we emphasize values of the DF which represent practical values of outage for current and future wireless systems. Contrary to some previous reports, our results show that the simpler Wilkinson's approach gives a more accurate estimate, in some cases of interest, than Schwartz and Yeh's (1982) approach. Overall, it is found that the Schleher's (1977) cumulants matching approach is a good method for small to medium dB spreads (/spl sigma/=6 dB), and Farley's approach is a good method for large dB spreads (/spl sigma/=12 dB).
机译:研究了四种可用于近似独立日志正常随机变量(RVS)之和的分布函数(DF)的方法进行研究。目的是确定考虑到准确性和计算工作的最佳方法来计算DF。调查侧重于DB扩散的值,/ SPL Sigma /,有效地用于无线传输中的实际问题(6 dB / SPL LES // SPL SIGMA // SPL LES / 12 dB)。同样,我们强调了DF的价值,代表了对当前和未来的无线系统中断的实际值。与此以前的一些报道相反,我们的结果表明,在某些兴趣的情况下,威尔克坦顿的方法更简单,比Schwartz和Yeh(1982)的方法在某些感兴趣的情况下提供更准确的估计。总的来说,发现斯凯尔的(1977)累积剂匹配方法是一个很好的方法,用于小于中等DB扩散(/ SPL Sigma / = 6 dB),而Farley的方法是大DB差价的好方法(/ SPL Sigma / = 12 dB)。

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