A systematic procedure for accurately approximating lognormal-sum distributions

Q. T. Zhang, S. H. Song

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

22 Citations (Scopus)

Abstract

Lognormal approximation to a sum of lognormal variables has been widely adopted in wireless communications, and its justification is based on the intuition that after taking a logarithm, a lognormal sum can converge to a Gaussian variable. In this paper, we show how to fit a lognormal sum with the best candidate from a large family of distributions, including the lognormal, by resorting to a systematic procedure of model selection and parameter estimation. It is found that, over a general parameter setting, a much better approximation for the lognormal sums in the log scale is given by the Pearson type-IV distribution whose parameters can easily be determined through simple arithmetic operations. Numerical examples are presented for illustration. © 2008 IEEE.
Original languageEnglish
Pages (from-to)663-666
JournalIEEE Transactions on Vehicular Technology
Volume57
Issue number1
DOIs
Publication statusPublished - Jan 2008

Research Keywords

  • Approximation to lognormal sums
  • Distribution selection
  • Lognormal approximation
  • Pearson system
  • Pearson type IV model

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