本主题介绍了一种基于人工智能的感知、定位和建模框架,该框架能够将信号、移动数据和数字孪生转化为适用于 6G 及未来网络的决策。它着重于在智慧城市等动态场景中进行实时推理,从而实现自适应资源利用、网络规划和自主优化。主要研究方向包括基础模型、生成式世界模型以及用于智能网络管理的集成感知通信。
This topic introduces an AI‑driven framework for sensing, localization, and modeling that converts signals, mobility data, and digital twins into decisions for 6G and beyond. It focuses on real‑time reasoning in dynamic scenarios like smart cities, enabling adaptive resource use, network planning, and autonomous optimization. Key interests include foundation models, generative world models, and integrated sensing‑communication for intelligent network management.