Reconfigurable Intelligent Surface MIMO Simulation using Quasi Deterministic Radio Channel Model

TL;DR

This paper adapts the QuaDRiGa radio channel generator for RIS-assisted MIMO system simulation, providing a geometry-consistent alternative to the traditional Rician model, and enabling more accurate and standardized evaluations.

Contribution

It introduces a novel method to simulate RIS-assisted systems using QuaDRiGa, ensuring geometry consistency and 3GPP standard compliance, unlike the commonly used Rician model.

Findings

QuaDRiGa provides spatially consistent large-scale fading.

The method supports user mobility and scenario calibration.

Results show geometry-inconsistent Rician models overestimate achievable rate.

Abstract

Reconfigurable Intelligent Surface (RIS) is a planar array that can control reflection and thus can implement the concept of partially controllable propagation environment. RIS received a lot of attention from industry and academia, but the majority of the researchers who study RIS-assisted systems use simple Rician model. Though it is suitable for theoretical analysis, stochastic Non Line-of-Sight (NLoS) component in Rician model does not account for the geometry of deployment. Furthermore, Rician model is not eligible to evaluate 3GPP standardization proposals. In this article we adapt the popular Quasi Deterministic Radio channel Generator (QuaDRiGa) for RIS-assisted systems and compare it against Rician model. The comparison shows that geometry-inconsistent NLoS Rician modeling results in higher estimated achievable rate. Our method, in contrast, inherits the advantages of QuaDRiGa: spatial consistency of Large Scale Fading, User Equipment mobility support as well as consistency between Large Scale and Small Scale Fading. Moreover, QuaDRiGa comes with calibrated scenario parameters that ensure 3GPP compatibility. Finally, the proposed method can be applied to any model or software originally designed for conventional MIMO, so every researcher can use it to build a simulation platform for RIS-assisted systems.