DocumentCode :
1355775
Title :
An MGF-Based Unified Framework to Determine the Joint Statistics of Partial Sums of Ordered Random Variables
Author :
Nam, Sung Sik ; Alouini, Mohamed-Slim ; Yang, Hong-Chuan
Author_Institution :
Dept. of Electr. & Comput. Eng., Texas A&M Univ., College Station, TX, USA
Volume :
56
Issue :
11
fYear :
2010
Firstpage :
5655
Lastpage :
5672
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.
Keywords :
fading channels; probability; signal processing; statistical analysis; MGF; fading channels; joint statistics; moment generating function; ordered random variables; probability density function; signal processing; wireless communication system; Diversity reception; Fading; Joints; Laplace equations; Probability density function; Random variables; Wireless communication; Joint PDF; Rayleigh fading; moment generating function (MGF); order statistics; probability density function (PDF);
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.2010.2070271
Filename :
5605378
Link To Document :
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