Centralized RAN Data Repository for Network Optimization
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Solution Overview
Problem
Current wireless communication systems, particularly in 5G NR, face challenges in efficiently managing and optimizing Radio Access Network (RAN) data across network entities, leading to suboptimal performance and increased complexity in data management.
Innovation Solution
A method and apparatus for storing and transmitting RAN-related information between network entities, utilizing a data repository in the core network to centralize RAN data and facilitate AI/ML-based analytics for optimization, thereby improving data management and network performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If RAN data is distributed across multiple network entities, then data management complexity is reduced at each entity, but overall system efficiency and optimization capability deteriorate
Solution Approach 1:
The patent consolidates RAN data from multiple distributed network entities into a centralized data repository within the core network. This merging approach maintains low complexity at individual entities while enabling system-wide optimization through centralized analytics and AI/ML processing, thereby resolving the contradiction between distributed simplicity and centralized efficiency.
2Productivity
If RAN data is centralized in the core network, then AI/ML-based analytics capability is improved, but data transmission and storage burden increases
Solution Approach 1:
The patent extracts only the essential RAN performance data and metrics required for AI/ML analytics from the complete set of RAN data. This selective extraction reduces the volume of data transmitted to and stored in the centralized repository while preserving the analytical value needed for network optimization, thus resolving the contradiction between analytics capability and data burden.
3Speed
If RAN entities maintain local data storage, then data access speed is improved, but network-wide optimization capability deteriorates
Solution Approach 1:
The patent implements a segmented data architecture where RAN entities maintain local caches for frequently accessed data (ensuring fast local access) while simultaneously contributing to and accessing the centralized data repository (enabling network-wide optimization). This segmentation allows both local responsiveness and global optimization to coexist, resolving the contradiction between access speed and optimization capability.
Data Source
AI summary
A second network entity/RAN entity may transmit to a first network entity/ADRF, and the first network entity/ADRF may receive from the second network entity/RAN entity, first information associated with a RAN. The first network entity/ADRF may store, at the first network entity/ADRF, the first information associated with the RAN. The first network entity/ADRF may transmit to the second network entity, and the second network entity may receive from the first network entity/ADRF, a response indicative of storage of the first information at the first network entity/ADRF. The first network entity/ADRF may receive, from a third network entity, a request for second information associated with the RAN. The first network entity/ADRF may transmit, to the third network entity, at least some of the second information associated with the RAN based on the request for the second information.