Show simple item record

dc.contributor.authorNam, Sungsik
dc.contributor.authorAlouini, Mohamed-Slim
dc.contributor.authorYang, Hongchuan
dc.date.accessioned2015-08-02T09:14:05Z
dc.date.available2015-08-02T09:14:05Z
dc.date.issued2010-11
dc.identifier.citationNam, S. S., Alouini, M.-S., & Yang, H.-C. (2010). An MGF-Based Unified Framework to Determine the Joint Statistics of Partial Sums of Ordered Random Variables. IEEE Transactions on Information Theory, 56(11), 5655–5672. doi:10.1109/tit.2010.2070271
dc.identifier.issn00189448
dc.identifier.doi10.1109/TIT.2010.2070271
dc.identifier.urihttp://hdl.handle.net/10754/561554
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.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectJoint PDF
dc.subjectmoment generating function (MGF)
dc.subjectorder statistics
dc.subjectprobability density function (PDF)
dc.subjectRayleigh fading
dc.titleAn MGF-based unified framework to determine the joint statistics of partial sums of ordered random variables
dc.typeArticle
dc.contributor.departmentCommunication Theory Lab
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.contributor.departmentPhysical Science and Engineering (PSE) Division
dc.identifier.journalIEEE Transactions on Information Theory
dc.contributor.institutionDepartment of Electronic Engineering, Hanyang University, Seoul, South Korea
dc.contributor.institutionDepartment of Electrical and Computer Engineering, University of Victoria, Victoria, BC V8W 3P6, Canada
dc.identifier.arxivid1008.2297
kaust.personAlouini, Mohamed-Slim


This item appears in the following Collection(s)

Show simple item record