Stochastic Geometric Analysis of IRS-aided Wireless Networks Using Mixture Gamma Model

An intelligent propagation environment is in massive demand to achieve ubiquitous connectivity for future wireless networks. One novel approach to resolve this demand is by utilizing passive intelligent reflective surfaces (IRS) that can operate with negligible energy and be deployed at low cost. Due to these properties, IRS has recently gained immense attention in the research community and has been studied extensively. However, most of the published work focused on link-level performance without incorporating the impact of the co-channel interference. These limitations motivated us to evaluate the IRS-aided wireless network’s network performance by using a stochastic geometric framework. We utilized the Mixture Gamma model to represent arbitrary fading distribution and derived its statistics. We derived the outage probability in a closed form expression based on the proposed channel model and introduced a tight bound for asymptotic analysis. Our numerical results indicate that the Mixture Gamma model provides an excellent fit to diverse propagation environments, including the line of sight (LOS) and Non-LOS channel, and the majority of the well-known popular fading models.