Analysis of IRS-Assisted Downlink Wireless Networks Over Generalized Fading

Intelligent Reflecting Surface (IRS) is a communication technology that can control the phase shift and reflection of the incoming signal towards the destination, achieving high spectral efficiency at a low hardware cost. However, the IRS-assisted wireless networks pose fundamental challenges on statistical channel modeling. Communication assisted by the IRS takes the form of a mixture channel, composed of a direct link and cascaded link aided by the IRS, which is often intractable to analyze, requires advanced functions, such as Meijer’s G or Fox’s H functions, to describe, and only applies to a certain operating frequency or network environment. These limitations motivate the development of a tractable and highly accurate channel model for IRS-assisted wireless networks, but versatile enough to be applied to any frequency band and communication scenario given proper parameterization. To this end, we utilize the mixture Gamma distributions to model IRS-assisted communication and derive distributions of the mixture channel for both multiplicability and quadratic form. The system performance of the IRS-assisted wireless network is analyzed using stochastic geometry, and the approximation accuracy of the proposed channel model is validated through extensive numerical simulation. These results indicate that the mixture Gamma distribution-based approximation can greatly facilitate the modeling and analysis in IRS-assisted networks with high accuracy.