Simulation of machine learning-based 6G systems in virtual worlds
This work addresses simulation challenges for 6G systems in virtual worlds, which is incremental for telecommunications and machine learning applications.
The paper tackled the simulation of 6G systems using 3D virtual environments to improve performance and reduce overhead, presenting strategies for paired MIMO channels and multimodal data and providing beam selection simulation results.
Digital representations of the real world are being used in many applications, such as augmented reality. 6G systems will not only support use cases that rely on virtual worlds but also benefit from their rich contextual information to improve performance and reduce communication overhead. This paper focuses on the simulation of 6G systems that rely on a 3D representation of the environment, as captured by cameras and other sensors. We present new strategies for obtaining paired MIMO channels and multimodal data. We also discuss trade-offs between speed and accuracy when generating channels via ray tracing. We finally provide beam selection simulation results to assess the proposed methodology.