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

Handle URI:
http://hdl.handle.net/10754/561554
Title:
An MGF-based unified framework to determine the joint statistics of partial sums of ordered random variables
Authors:
Nam, Sungsik; Alouini, Mohamed-Slim ( 0000-0003-4827-1793 ) ; Yang, Hongchuan
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.
KAUST Department:
Electrical Engineering Program; Physical Sciences and Engineering (PSE) Division; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Communication Theory Lab
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
IEEE Transactions on Information Theory
Issue Date:
Nov-2010
DOI:
10.1109/TIT.2010.2070271
Type:
Article
ISSN:
00189448
Appears in Collections:
Articles; Physical Sciences and Engineering (PSE) Division; Electrical Engineering Program; Communication Theory Lab; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorNam, Sungsiken
dc.contributor.authorAlouini, Mohamed-Slimen
dc.contributor.authorYang, Hongchuanen
dc.date.accessioned2015-08-02T09:14:05Zen
dc.date.available2015-08-02T09:14:05Zen
dc.date.issued2010-11en
dc.identifier.issn00189448en
dc.identifier.doi10.1109/TIT.2010.2070271en
dc.identifier.urihttp://hdl.handle.net/10754/561554en
dc.description.abstractOrder 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.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.subjectJoint PDFen
dc.subjectmoment generating function (MGF)en
dc.subjectorder statisticsen
dc.subjectprobability density function (PDF)en
dc.subjectRayleigh fadingen
dc.titleAn MGF-based unified framework to determine the joint statistics of partial sums of ordered random variablesen
dc.typeArticleen
dc.contributor.departmentElectrical Engineering Programen
dc.contributor.departmentPhysical Sciences and Engineering (PSE) Divisionen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentCommunication Theory Laben
dc.identifier.journalIEEE Transactions on Information Theoryen
dc.contributor.institutionDepartment of Electronic Engineering, Hanyang University, Seoul, South Koreaen
dc.contributor.institutionDepartment of Electrical and Computer Engineering, University of Victoria, Victoria, BC V8W 3P6, Canadaen
kaust.authorAlouini, Mohamed-Slimen
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