• 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