An MGF-based unified framework to determine the joint statistics of partial sums of ordered random variables

Sungsik Nam, Mohamed-Slim Alouini, Hongchuan Yang

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

Order statistics find applications in various areas of communications and signal processing. In this paper, we introduce an unified analytical framework to determine the joint statistics of partial sums of ordered random variables (RVs). With the proposed approach, we can systematically derive the joint statistics of any partial sums of ordered statistics, in terms of the moment generating function (MGF) and the probability density function (PDF). Our MGF-based approach applies not only when all the K ordered RVs are involved but also when only the Ks(Ks < K) best RVs are considered. In addition, we present the closed-form expressions for the exponential RV special case. These results apply to the performance analysis of various wireless communication systems over fading channels. © 2006 IEEE.
Original languageEnglish (US)
Pages (from-to)5655-5672
Number of pages18
JournalIEEE Transactions on Information Theory
Volume56
Issue number11
DOIs
StatePublished - Nov 2010

ASJC Scopus subject areas

  • Library and Information Sciences
  • Information Systems
  • Computer Science Applications

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