  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.
