A.S. Al-Hussien∗ and M.M. Banat∗∗
Joint density functions, joint distribution functions, Nakagami fad- ing, generalized selection combining, diversity communications re- ceivers
This paper deals with a problem in which the joint statistics of a set of N random variables are known. Based on this knowledge, we derive the joint probability density function (PDF) of the L largest random variables (L ≤ N). The N random variables will be assumed to be correlated and non-identically distributed. Problems typical to this one are normally encountered in the performance analysis of a certain class of receivers used in multipath fading channels with correlated and unbalanced diversity branches. In this application, the receiver has access to N signal-to-noise ratio (SNR) random variables, and it has to make a symbol decision based on the largest L SNRs. This class of receivers is widely known as generalized selection combining (GSC) receivers.
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