3D Modeling of Factory Scenarios for 5G Evaluations

Abstract: 5G is a key enabler for a variety of use cases in smart manufacturing which requires communications with high reliability and low latency. In a dynamic industrial environment, objects such as machines, production lines, storage shelves, robotic arms, and automatically guided vehicles may cause fading and have a large impact on radio propagation. With the state-of-the-art 3D graphics tool Omniverse and ray-tracing techniques from Nvidia, we could build digital 3D industrial environments with flexible layouts and enable complex radio propagation modeling inside. Highly accurate propagation models from Ericsson allow us to evaluate 5G radio network performance with high reliability and help understand the impact of different factors on the network performance. How to utilize the 3D graphics tools to facilitate the ray-tracing-based radio network simulation in terms of flexibility and efficiency is to be addressed. In this thesis, we develop a reliable Omniverse-based workflow to randomly generate flexible and representative 3D models of factories for 5G radio simulations. By utilizing the ray-tracing-based simulation tool from Ericsson, we investigate the relationship between simulation time consumption and model complexity, providing valuable insights for researchers to estimate the simulation time. Moreover, the impact of different antenna types and layout configurations on network performance and radio propagation is analyzed by leveraging the generated 3D factories as well. The study reveals the important role of antenna type and layout configuration in network performance and radio propagation. These findings hold significant implications for the deployment and design of wireless networks in dynamic industrial environments. In addition, the approach presented in this thesis offers a reproducible and adaptable template for generating various 3D scenarios for simulations, facilitating further exploration of 5G network performance in diverse environments. This approach also enhances the current network simulation workflow at Ericsson, enabling researchers to efficiently and accurately evaluate 5G radio network performance in dynamic industrial environments and other scenarios for practical deployment.