Asymptotic Maximum Order Statistic for SIR in ${\kappa} -{\mu}$ Shadowed Fading

Abstract

Using tools from extreme value theory (EVT), it is proved that when the user signal and the interferer signals undergo independent and non-identically distributed (i.n.i.d.) $\kappa -\mu $ shadowed fading, the limiting distribution of the maximum of $L$ independent and identically distributed (i.i.d.) signal-to-interference ratio (SIR) random variables (RVs) is a Frechet distribution. It is observed that this limiting distribution is close to the true distribution of maximum for maximum SIR evaluated over moderate $L$ . Furthermore, moments of the maximum RV is shown to converge to the moments of the Frechet RV. In addition, the rate of convergence of the actual distribution of the maximum to the Frechet distribution is derived and analyzed for different $\kappa $ and $\mu $ parameters. Finally, results from the stochastic ordering are used to analyze the variation in the limiting distribution with respect to the variation in source fading parameters. These results are then used to derive upper bound for the rate in full array selection (FAS) schemes for the antenna selection and the asymptotic outage probability and the ergodic rate in maximum-sum-capacity (MSC) scheduling systems.