Research on the evolution, key technologies, and applications for AI enabled 5G-Advanced core network running

5G serves as the pivotal infrastructure for the emerging era of the Internet of everything, with intelligentization being its crucial direction. In the 5G-Advanced (5G-A) phase, AI enabled core network running can substantially enhance network efficiency, facilitate real-time perception, and precisely cater to diversified service demands through the deep integration of AI technology and network running mechanisms. For the 5G-A network, the overall intelligent architecture, key technologies, and applications of AI enabled core network operations were highlighted. Firstly, the development trend of AI enabled 5G-A core network running was analyzed and key intelligent applications were elaborated. Secondly, AI enabled core network running architecture combining four layers and four dimensions was proposed, encompassing a central intelligent analysis layer, a control plane intelligent endogenous layer, an edge real-time inference layer, and an on-device lightweight inference layer. This architecture enables customized, real-time data collection across four dimensions: slices, network elements, users, and service flows, thereby offering intelligent analysis services such as data perception, training, and inference. Then, five key technologies and capabilities of AI enabled core network running were introduced. Finally, focusing on the typical service requirements of AI enabled core network running, the relevant solutions and their results were analyzed and summarized, thus providing new ideas for the application and implementation of 5G-A core network intelligence.

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-12-01
Primary Topic
Advanced Wireless Communication Technologies
Type
article
Field-Weighted Citation Impact
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article

Research on the evolution, key technologies, and applications for AI enabled 5G-Advanced core network running

SHILAP Revista de lepidopterología
Advanced Wireless Communication Technologies
article

Research on the evolution, key technologies, and applications for AI enabled 5G-Advanced core network running

article en

Abstract

5G serves as the pivotal infrastructure for the emerging era of the Internet of everything, with intelligentization being its crucial direction. In the 5G-Advanced (5G-A) phase, AI enabled core network running can substantially enhance network efficiency, facilitate real-time perception, and precisely cater to diversified service demands through the deep integration of AI technology and network running mechanisms. For the 5G-A network, the overall intelligent architecture, key technologies, and applications of AI enabled core network operations were highlighted. Firstly, the development trend of AI enabled 5G-A core network running was analyzed and key intelligent applications were elaborated. Secondly, AI enabled core network running architecture combining four layers and four dimensions was proposed, encompassing a central intelligent analysis layer, a control plane intelligent endogenous layer, an edge real-time inference layer, and an on-device lightweight inference layer. This architecture enables customized, real-time data collection across four dimensions: slices, network elements, users, and service flows, thereby offering intelligent analysis services such as data perception, training, and inference. Then, five key technologies and capabilities of AI enabled core network running were introduced. Finally, focusing on the typical service requirements of AI enabled core network running, the relevant solutions and their results were analyzed and summarized, thus providing new ideas for the application and implementation of 5G-A core network intelligence.

SHILAP Revista de lepidopterología
Industry, innovation and infrastructure
Openalex Percentile: Top 64%
Advanced Wireless Communication Technologies
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Research on the evolution, key technologies, and applications for AI enabled 5G-Advanced core network running · SHILAP Revista de lepidopterología (2024) | TGRS Research Map | TGRS