An MGF-based unified framework to determine the joint statistics of partial sums of ordered random variables
Type
ArticleKAUST Department
Communication Theory LabComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Physical Science and Engineering (PSE) Division
Date
2010-11Permanent link to this record
http://hdl.handle.net/10754/561554
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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.Citation
Nam, 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.2010.2070271arXiv
1008.2297ae974a485f413a2113503eed53cd6c53
10.1109/TIT.2010.2070271