论文标题
6G数字双网络：从理论到实践
6G Digital Twin Networks: From Theory to Practice
论文作者
论文摘要
数字双网络（DTN）是物理网络的实时复制品。它们正在成为一种强大的技术，用于设计，诊断，模拟，假设分析以及人工智能（AI）/机器学习（ML）驱动的实时优化和对第六代（6G）无线网络的控制。尽管数字双胞胎可以为6G提供什么潜力，但意识到6G DTN的所需功能需要解决许多设计方面，包括数据，模型和接口。在本文中，我们通过介绍杰出的用例及其服务要求，描述参考架构并讨论基本设计方面来提供6G DTN的概述。我们还提出了一个现实世界的示例，以说明如何在实时参考开发平台Omniverse中建立和操作DTN。
Digital twin networks (DTNs) are real-time replicas of physical networks. They are emerging as a powerful technology for design, diagnosis, simulation, what-if-analysis, and artificial intelligence (AI)/machine learning (ML) driven real-time optimization and control of the sixth-generation (6G) wireless networks. Despite the great potential of what digital twins can offer for 6G, realizing the desired capabilities of 6G DTNs requires tackling many design aspects including data, models, and interfaces. In this article, we provide an overview of 6G DTNs by presenting prominent use cases and their service requirements, describing a reference architecture, and discussing fundamental design aspects. We also present a real-world example to illustrate how DTNs can be built upon and operated in a real-time reference development platform - Omniverse.
