This article presents a vision where \textit{real-time} digital twins of the physical wireless environments are continuously updated using multi-modal sensing data from the distributed infrastructure and user devices, and are used to make communication and sensing decisions. This vision is mainly enabled by the advances in precise 3D maps, multi-modal sensing, ray-tracing computations, and machine/deep learning. This article details this vision, explains the different approaches for constructing and utilizing these real-time digital twins, discusses the applications and open problems, and presents a research platform that can be used to investigate various digital twin research directions.
翻译:本文展示了一种愿景,即实际无线环境中的 \ textit{ 实时} 数字双胞胎利用分布式基础设施和用户装置的多模式遥感数据不断更新,并用于做出通信和遥感决定。这一愿景主要得益于精确的 3D 地图、多模式遥感、光测算和机器/深层学习的进步。 文章详细介绍了这一愿景,解释了建造和利用这些实时数字双胞胎的不同方法,讨论了应用程序和开放问题,并提供了一个研究平台,可用于调查各种数字双向研究方向。