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GenAI and knowledge driven 5G operations

URN C23.0.537
Topics 5G, AI (Artificial Intelligence), Autonomous networks

Successfully applied to two provinces of China Unicom, improving O&M efficiency by over 10 times. Fault demarcation accuracy is over 95%.

To achieve the level of network intelligence required of the 5G era, CSPs must use advanced AI to detect, diagnose and resolve network performance issues. This Catalyst aims to develop an intelligent cognitive decision-making system for 5G network operation, which will help to improve network performance, reduce operational costs, and enhance customer experience. The system will automatically collect and process network data, classify and analyze root causes through the pre-trained AI model, and automatically delimit and locate problems in combination with network resource database. Then, it will match the solution through the decision knowledge base, form the intention with the resource base, and send it to the network management system to identify the intention and perform operations on the network. After the implementation, the algorithm model and knowledge base will be self-optimized and self-learning according to the implementation results.


C23.0.537 Introduction -GenAI and knowledge driven 5G operations

Inform feature

Using GenAI and knowledge graphs to transform network operations and maintenance

Introduction document

C23.0.537 GenAI and knowledge driven 5G operations --well-presented

C23.0.537 GenAI and knowledge driven 5G operations --detailed


Case 1:Automatic adjustment of antenna weight

Main promotional video

Case2:Cross-operator VoNR voice optimization

Demo:Communication Knowledge Base

Contact team

Email the members of the Catalyst team to request more details.


Team members

Beijing ZZNode Technologies Co.,Ltd. logo
China Telecommunications Corporation logo
China Unicom logo
Inspur Communication Information Systems Co., Ltd logo
ZTE Corporation logo

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