面向6G无线系统的数字孪生网络：架构、使能技术、智能控制与开放挑战
Digital Twin Networks for 6G Wireless Systems: Architecture, Enabling Technologies, Intelligent Control, and Open Challenges
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中文总结 AI 辅助
该综述针对6G网络需求，将数字孪生网络（DTN）架构分为被动监测与主动控制两类，分析其使能技术与计算复杂度，关联6G应用场景，指出硬件、延迟与安全挑战并给出研究方向。
中文摘要 AI 辅助
向第六代（6G）移动网络过渡需要主动且确定性的编排，以满足未来服务严苛的关键性能指标，包括超可靠低延迟通信、增强移动宽带和大规模机器类通信。数字孪生网络（Digital Twin Networks，DTN）近年来成为满足这些需求的基础技术，可提供物理网络的实时高保真虚拟副本。尽管现有文献已从概念上探讨了DTN，但在技术分类和计算可行性评估方面仍存在空白。本综述通过将最新DTN架构正式分类为被动监测孪生和主动控制孪生，填补了这一空白。我们深入评估了其底层使能技术，具体包括射线追踪、可重构智能表面、人工智能和移动边缘计算。重要的是，本文对最新解决方案进行了详细的数学和计算复杂度分析，以评估硬件可扩展性和推理瓶颈。随后将这些架构与各种即将到来的6G用例关联，包括智慧城市、工业5.0、医疗保健和智能电网。最后，我们综合了关键的未解决挑战，强调了图形处理单元硬件限制、信息物理执行延迟以及零信任安全范式的需求，并为实现统一的万物互联网提供了战略研究方向。
英文摘要
The transition to the Sixth Generation (6G) of mobile networks requires proactive and deterministic orchestration to satisfy the stringent key performance indicators of future services, including ultra-reliable low-latency communications, enhanced mobile broadband, and massive machine-type communications. Digital Twin Networks (DTN) have recently emerged as a foundational technology to meet these demands, offering real-time and high-fidelity virtual replicas of the physical network. Although the current literature explores DTNs conceptually, a gap exists in the coverage of technical classification and computational feasibility evaluations. This survey addresses this gap by formally categorizing state-of-the-art DTN architectures into passive monitoring twins and active control twins. We provide an in-depth evaluation of their underlying enabling technologies, specifically ray-tracing, reconfigurable intelligent surfaces, artificial intelligence, and mobile edge computing. Importantly, this paper conducts a detailed mathematical and computational complexity analysis of state-of-the-art solutions to assess hardware scalability and inference bottlenecks. These architectures are then linked to various forthcoming 6G use cases, including smart cities, Industry 5.0, healthcare, and smart grids. Finally, we synthesize crucial unresolved challenges, highlighting graphics processing unit hardware limitations, cyber-physical actuation latency, and the need for a zero-trust security paradigm, offering strategic research directions to realize the unified internet of everything.
