Show simple item record

dc.contributor.authorNam, Sungsik
dc.contributor.authorYang, Hongchuan
dc.contributor.authorAlouini, Mohamed-Slim
dc.contributor.authorKim, Dongin
dc.date.accessioned2015-08-03T12:06:04Z
dc.date.available2015-08-03T12:06:04Z
dc.date.issued2014-08
dc.identifier.citationNam, S. S., Yang, H.-C., Alouini, M.-S., & Kim, D. I. (2014). An MGF-Based Unified Framework to Determine the Joint Statistics of Partial Sums of Ordered i.n.d. Random Variables. IEEE Transactions on Signal Processing, 62(16), 4270–4283. doi:10.1109/tsp.2014.2326624
dc.identifier.issn1053587X
dc.identifier.doi10.1109/TSP.2014.2326624
dc.identifier.urihttp://hdl.handle.net/10754/563679
dc.description.abstractThe joint statistics of partial sums of ordered random variables (RVs) are often needed for the accurate performance characterization of a wide variety of wireless communication systems. A unified analytical framework to determine the joint statistics of partial sums of ordered independent and identically distributed (i.i.d.) random variables was recently presented. However, the identical distribution assumption may not be valid in several real-world applications. With this motivation in mind, we consider in this paper the more general case in which the random variables are independent but not necessarily identically distributed (i.n.d.). More specifically, we extend the previous analysis and introduce a new more general unified analytical framework to determine the joint statistics of partial sums of ordered i.n.d. RVs. Our mathematical formalism is illustrated with an application on the exact performance analysis of the capture probability of generalized selection combining (GSC)-based RAKE receivers operating over frequency-selective fading channels with a non-uniform power delay profile. © 1991-2012 IEEE.
dc.description.sponsorshipThis work was supported in part by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIP) (NRF-2014R1A5A1011478). This is an extended version of a paper which was presented at the IEEE International Symposium on Information Theory (ISIT 2013), Istanbul, Turkey, July 2013.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttp://arxiv.org/abs/arXiv:1307.8199v2
dc.subjectexponential distribution
dc.subjectjoint statistics
dc.subjectmoment generating function (MGF)
dc.subjectnon-identical distribution
dc.subjectOrder statistics
dc.subjectprobability density function (PDF)
dc.titleAn MGF-based unified framework to determine the joint statistics of partial sums of ordered i.n.d. random variables
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.contributor.departmentCommunication Theory Lab
dc.identifier.journalIEEE Transactions on Signal Processing
dc.contributor.institutionHanyang University, Seoul, South Korea
dc.contributor.institutionDepartment of Electrical and Computer Engineering, University of Victoria, Victoria, BC, Canada
dc.contributor.institutionSungkyunkwan University (SKKU), Suwon-city 440-746, South Korea
dc.identifier.arxivid1307.8199
kaust.personAlouini, Mohamed-Slim
dc.date.posted2013-07-31


This item appears in the following Collection(s)

Show simple item record