Ergodic Capacity and Outage Probability Analysis for Multiple Intelligent Reflecting Surface Assisted Wireless Networks

Due to location-specific geometrical properties and time-dependent vehicular traffic, many urban area segments exhibit diverse fading patterns. This research examines the ergodic capacity and outage probability estimate for these segments. Several Intelligent Reflecting Surface (IRS) panels installed on roadside infrastructure are present in these geographical regions. Various application scenarios are examined when the receiver is exposed to reflected and direct Line-of-Sight links, which are defined by \(\kappa -\mu\) $\kappa -\mu$ shadowed fading. An approximation analysis of the studied \(\kappa -\mu\) $\kappa -\mu$ shadowed fading channel via Nakagami-m fading model and an exact study of the impact of \(\kappa -\mu\) $\kappa -\mu$ shadowed fading on the ergodic capacity and outage probability of the wireless link are presented using Monte Carlo simulation. In order to confirm the effectiveness of IRS panel deployment, one of the governing factors is the average signal-to-noise ratio. When accounting for the dynamics of the vehicle traffic, an improved ergodic capacity and outage probability estimate show the value of placing IRS panels at any point within the examined geographic segments.