论文标题
模拟虚拟世界中基于机器学习的6G系统
Simulation of machine learning-based 6G systems in virtual worlds
论文作者
论文摘要
现实世界的数字表示形式已用于许多应用程序，例如增强现实。 6G系统不仅将支持依赖虚拟世界的用例，而且还会从其丰富的上下文信息中受益，以提高性能并减少沟通开销。本文着重于依赖于环境的3D表示的6G系统的模拟，该系统由相机和其他传感器捕获。我们提出了获得配对的MIMO通道和多模式数据的新策略。通过射线跟踪生成频道时，我们还讨论了速度和准确性之间的权衡。我们最终提供了光束选择模拟结果，以评估所提出的方法。
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.
