DTRAN：利用数字孪生进行RAN优化的特殊用例
DTRAN: A Special Use Case of RAN Optimization using Digital Twin
AI总结：
本文提出DTRAN框架，利用数字孪生以从核心到边缘的整体方式实现实时数据管理与物理网络通信，并通过RAN配置优化用例验证其在真实场景中的适用性。
摘要：
超5G（B5G）和6G网络的出现凸显了先进计算机辅助工具（如网络数字孪生（DT））在促进自治网络和泛在智能方面的关键作用。数字孪生领域的现有解决方案主要旨在对网络生命周期内的特定任务进行建模和自动化，这缺乏完全自主设计和管理的灵活性与适应性。与现有的数字孪生方法不同，我们提出了利用数字孪生进行RAN优化（DTRAN）框架，该框架遵循从核心网到边缘网络的整体方法。所提出的DTRAN框架实现了与物理网络的实时数据管理和通信，从而提供了比现有方法更准确、更详细的数字副本。我们概述了DTRAN的主要构建模块，并描述了我们具体用例（即RAN配置优化）的细节，以证明所提出框架在真实场景中的适用性。
英文摘要：
The emergence of beyond 5G (B5G) and 6G networks underscores the critical role of advanced computer-aided tools, such as network digital twins (DTs), in fostering autonomous networks and ubiquitous intelligence. Existing solutions in the DT domain primarily aim to model and automate specific tasks within the network lifecycle, which lack flexibility and adaptability for fully autonomous design and management. Unlike the existing DT approaches, we propose RAN optimization using the Digital Twin (DTRAN) framework that follows a holistic approach from core to edge networks. The proposed DTRAN framework enables real-time data management and communication with the physical network, which provides a more accurate and detailed digital replica than the existing approaches. We outline the main building blocks of the DTRAN and describe the details of our specific use case, which is RAN configuration optimization, to demonstrate the applicability of the proposed framework for a real-world scenario.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
