6G网络场景下AI赋能的网络切片技术分析及展望OA

As 6G networks evolve toward ubiquitous coverage,inherent intelligence,and on-demand services,network slicing emerges as a key enabling technology.By leveraging virtualization and software-defined networking,it logically partitions physical networks to meet customized requirements across diverse scenarios.However,the ultra-large scale,dynamic topology,and service burstiness of 6G networks pose challenges to traditional slicing approaches,and the integration of artificial intelligence becomes an inevitable trend.Against this backdrop,this paper systematically reviews AI-enabled net-work slicing technologies.First,it introduces the core vision,application scenarios,and the"three-layer six-faced architec-ture"design of 6G networks,establishing a foundational framework for technical analysis.Next,it elucidates the concept,end-to-end architecture,and key technologies of network slicing,clarifying the core logic of slicing technology.Subse-quently,it classifies and summarizes AI-enabled network slicing research based on the differences in methodologies employed.Finally,addressing the evolving network requirements for 6G,the paper dissects the core challenges facing AI-enabled network slicing research and proposes potential solutions,offering guidance for future research directions.