Artificial intelligence(AI)-native communication is considered one of the key technologies for the development of 6G mobile communication networks.This paper investigates the architecture for developing the network da...Artificial intelligence(AI)-native communication is considered one of the key technologies for the development of 6G mobile communication networks.This paper investigates the architecture for developing the network data analytics function(NWDAF)in 6G AI-native networks.The architecture integrates two key components:data collection and management,and model training and management.It achieves real-time data collection and management,establishing a complete workflow encompassing AI model training,deployment,and intelligent decision-making.The architecture workflow is evaluated through a vertical scaling use case by constructing an AI-native network testbed on Kubernetes.Within this proposed NWDAF,several machine learning(ML)models are trained to make vertical scaling decisions for user plane function(UPF)instances based on data collected from various network functions(NFs).These decisions are executed through the Ku-bernetes API,which dynamically allocates appropriate resources to UPF instances.The experimental results show that all implemented models demonstrate satisfactory predictive capabilities.Moreover,compared with the threshold-based method in Kubernetes,all models show a significant advantage in response time.This study not only introduces a novel AI-native NWDAF architecture but also demonstrates the potential of AI models to significantly improve network management and resource scaling in 6G networks.展开更多
The issues of wireless communication network autonomy,the definition of capability level and the concept of AI-native solution based on the integration of the information communication data technology(ICDT)are first i...The issues of wireless communication network autonomy,the definition of capability level and the concept of AI-native solution based on the integration of the information communication data technology(ICDT)are first introduced in this paper.A series of innovative technologies proposed by ZTE Corporation,such as an autonomous evolution network and intelligent orchestration network,are then analyzed.These technologies are developed to realize the evolution of wireless networks to Level-4 and Level-5 intelligent networks.It is expected that the future AI-native intelligent network system will be built based on innovative technologies such as digital twins,intent-based networking,and the data plane and intelligent plane.These new technical paradigms will promote the development of intelligent B5G and 6G networks.展开更多
Artificial intelligence(AI)and wireless communications are catalyzing each other’s advancement as we approach 6G networks and beyond.This article presents a perspective on the two-way interplay between AI and communi...Artificial intelligence(AI)and wireless communications are catalyzing each other’s advancement as we approach 6G networks and beyond.This article presents a perspective on the two-way interplay between AI and communications-how AI techniques are revolutionizing communication network design(AI4Comm)and how emerging communication technologies are enabling and accelerating AI(Comm4AI).We discuss recent advances and outline the challenges in realizing an AI-native wireless ecosystem and propose a roadmap for integrating AI and communications,offering insights into a future where wireless communications and AI evolve together.展开更多
基金supported by the National Key Research and Development Program of China under Grant No.2023YFE0200700National Natural Science Foundation of China under Grant No.62171474ZTE Industry University-Institute Cooperation Funds under Grant No.IA20241014013。
文摘Artificial intelligence(AI)-native communication is considered one of the key technologies for the development of 6G mobile communication networks.This paper investigates the architecture for developing the network data analytics function(NWDAF)in 6G AI-native networks.The architecture integrates two key components:data collection and management,and model training and management.It achieves real-time data collection and management,establishing a complete workflow encompassing AI model training,deployment,and intelligent decision-making.The architecture workflow is evaluated through a vertical scaling use case by constructing an AI-native network testbed on Kubernetes.Within this proposed NWDAF,several machine learning(ML)models are trained to make vertical scaling decisions for user plane function(UPF)instances based on data collected from various network functions(NFs).These decisions are executed through the Ku-bernetes API,which dynamically allocates appropriate resources to UPF instances.The experimental results show that all implemented models demonstrate satisfactory predictive capabilities.Moreover,compared with the threshold-based method in Kubernetes,all models show a significant advantage in response time.This study not only introduces a novel AI-native NWDAF architecture but also demonstrates the potential of AI models to significantly improve network management and resource scaling in 6G networks.
文摘The issues of wireless communication network autonomy,the definition of capability level and the concept of AI-native solution based on the integration of the information communication data technology(ICDT)are first introduced in this paper.A series of innovative technologies proposed by ZTE Corporation,such as an autonomous evolution network and intelligent orchestration network,are then analyzed.These technologies are developed to realize the evolution of wireless networks to Level-4 and Level-5 intelligent networks.It is expected that the future AI-native intelligent network system will be built based on innovative technologies such as digital twins,intent-based networking,and the data plane and intelligent plane.These new technical paradigms will promote the development of intelligent B5G and 6G networks.
基金supported in part by the National Natural Science Foundation of China under Grants 62341101,62125101,and 62301011in part by Beijing Natural Science Foundation under Grant L257016in part by the New Cornerstone Science Foundation through the Xplorer Prize.
文摘Artificial intelligence(AI)and wireless communications are catalyzing each other’s advancement as we approach 6G networks and beyond.This article presents a perspective on the two-way interplay between AI and communications-how AI techniques are revolutionizing communication network design(AI4Comm)and how emerging communication technologies are enabling and accelerating AI(Comm4AI).We discuss recent advances and outline the challenges in realizing an AI-native wireless ecosystem and propose a roadmap for integrating AI and communications,offering insights into a future where wireless communications and AI evolve together.
