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Work item:
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Y.KNO
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Subject/title:
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Requirements and framework for knowledge-based network optimization in IMT-2020 networks and beyond
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Status:
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[Carried to next study period]
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Approval process:
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AAP
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Type of work item:
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Recommendation
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Version:
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New
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Equivalent number:
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-
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Timing:
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-
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Liaison:
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ITU-T SG16, IEEE Knowledge Graph Working Group, ETSI ENI, 3GPP
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Supporting members:
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China Unicom, China Telecom, China Information Communication Technologies Group Corporation, Peng Cheng Laboratory, BUPT
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Summary:
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In this draft Recommendation, knowledge refers to network knowledge graphs and knowledge models constructed based on multimodal data, such as network data, network topology, expert experience, etc. Knowledge has apriority and universality. Based on the apriority of knowledge, the training speed and accuracy of AI/ML models can be enhanced in the process of network optimization policy generation and root cause diagnostic. Based on the universality of knowledge, the knowledge formed in one scenario can be reused and evolved to improve the efficiency of relevant network optimization tasks.
Currently, there are several work items in ITU-T that address the utilization of knowledge-related technologies to enhance the intelligence level of the networks. Such work items mainly focus on the mechanism of knowledge construction in big data driven network, the specification of knowledge base in autonomous network, and the management aspect of knowledge in telecom operation.
This draft Recommendation will further study how to provide and utilize knowledge enhancement functional capabilities within the architecture of IMT-2020 networks and beyond. The objective is to realize knowledge-based network optimization through closed loop capabilities of network traffic awareness, intelligent intent perception, network knowledge construction, and knowledge-based network optimization policy generation and verification.
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Comment:
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-
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Reference(s):
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Historic references:
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Contact(s):
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| ITU-T A.5 justification(s): |
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First registration in the WP:
2024-03-21 10:01:50
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Last update:
2024-09-19 10:50:01
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