Ray tracing based 6G reconfigurable intelligent surface modelling

Abstract

Ray tracing accelerated with graphics processing units (GPUs) is an increasingly popular technique for accurate and efficient simulation of wireless communication channels. In this thesis, we extend the GPU-accelerated Ray Tracer from the AIT Austrian Institute of Technology to support the effects of reconfigurable intelligent surfaces (RISs), a modern technology aimed at solving propagation issues in the higher frequency bands of sixth- generation cellular networks (6G).The AIT Ray Tracer implements a two-stage hybrid ray tracing method to simulate the propagation of electromagnetic waves in complex environments. We propose an approach for integrating RISs into the Ray Tracer by launching rays toward the individual RIS patch antenna elements. The electric field of the rays is manipulated and reflected upon intersection with the RIS. To evaluate the electric field, we derived a compartmentalized RIS path loss model. The flexibility of our model is easily integrated into the Ray Tracer and enables further extensions for the implementation of additional features and incorporation into more complex scenarios.Through a comparison with measurements and an empirically established numerical model, we verified the derivation and implementation of our model. In addition, we demonstrated the capabilities of our compartmentalized model by extending the Ray Tracer to support higher-order reflections from the RIS to the receiver. We found that such components had a significant effect on the received signal strength, concluding that the extensions of advanced functionality enabled by our model play an important role in the accurate modeling of reconfigurable intelligent surfaces.