Abstract
Reconfigurable intelligent surfaces (RISs) are emerging as a key enabler of 6 G wireless systems, offering the potential to significantly enhance signal propagation and network performance. This paper presents a novel approach for modeling RIS-assisted millimeter-wave communication channels using a Gamma-distributed approximation. By modeling the channel gains between the base station, RIS, and user as Gamma random variables, the proposed method captures both line-of-sight conditions and shadowing effects effectively. We derive closed-form expressions for two critical performance metrics, such as outage probability (OP) and ergodic capacity, along with their corresponding upper and lower bounds. The analytical results are validated through extensive Monte Carlo simulations, demonstrating close agreement between the approximation and simulation data. Furthermore, we observe that the accuracy of the Gamma approximation improves as the number of RIS elements increases, and the OP bounds tighten under less severe channel conditions.