Hierarchical NWDAF Architecture for 5G Network Slice Analytics
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Solution Overview
Problem
The current 5G network lacks sufficient intelligence to realize on-demand service and optimize network resource utilization, leading to complexity in meeting diverse and individualized service requirements in complex communication scenarios.
Innovation Solution
A two-level hierarchical Network Data Analytics Function (NWDAF) architecture is deployed, where first-level NWDAF elements collect and analyze shared data across multiple network slices, and second-level NWDAF elements perform analysis on monopolized data within individual slices, enabling efficient data collection, association, and feedback to optimize network parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a traditional flat NWDAF architecture is used, then the system structure is simple, but it cannot meet diversified service requirements and individualized service experiences
Solution Approach 1:
The patent divides the flat NWDAF architecture into a two-level hierarchical structure: first-level NWDAF elements handle macro-level network-wide analytics, while second-level NWDAF elements handle slice-specific analytics. This segmentation allows the system to meet diversified service requirements for different network slices while maintaining manageable complexity through clear division of responsibilities between levels.
Solution Approach 2:
The patent introduces a hierarchical dimension to the previously flat architecture, creating vertical layers (first-level and second-level NWDAF elements) while maintaining horizontal connections. This dimensional transformation enables the system to handle both network-wide and slice-specific analytics simultaneously, improving adaptability without linearly increasing complexity.
2Reliability
If network-wide centralized analysis is performed, then data security is reduced, but comprehensive network optimization can be achieved
Solution Approach 1:
The patent segments data processing responsibilities between first-level and second-level NWDAF elements. Second-level elements process slice-specific data locally, enhancing data security by keeping sensitive slice data within the slice. First-level elements receive aggregated results for network-wide optimization, maintaining optimization efficiency without requiring access to all raw slice data.
Solution Approach 2:
The first-level NWDAF elements act as intermediaries between second-level elements and the network management system. They aggregate and synthesize analytics results from multiple slices, providing comprehensive network optimization insights while protecting individual slice data security through the intermediary aggregation layer.
3Reliability
If individualized service analysis is performed for each network slice, then data security is improved, but network-wide optimization capability is reduced
Solution Approach 1:
The patent segments analytics functionality into slice-specific second-level NWDAF elements that maintain data security by processing only their assigned slice data, and first-level NWDAF elements that aggregate results for network-wide optimization. This segmentation enables both individualized service analysis and network-wide optimization to coexist.
Solution Approach 2:
The patent merges the analytics capabilities of multiple second-level NWDAF elements at the first-level elements. By combining aggregated results from various slices, the system achieves network-wide optimization insights while each individual second-level element maintains data security by processing only its assigned slice data.
4Productivity
If a two-level hierarchical NWDAF architecture is deployed, then network resource utilization is improved, but system complexity increases
Solution Approach 1:
The patent segments the analytics processing workload between first-level and second-level NWDAF elements, enabling efficient resource utilization by assigning specific tasks to appropriate levels. Second-level elements handle slice-specific analytics, while first-level elements handle aggregation and network-wide optimization, improving overall resource utilization despite increased architectural complexity.
Solution Approach 2:
The first-level NWDAF elements serve multiple functions: they aggregate results from second-level elements, perform network-wide analytics, and provide optimization recommendations. This multi-functionality at the first level justifies the hierarchical structure by demonstrating how the additional layer enables both slice-specific and network-wide optimization capabilities.
Data Source
AI summary
A data analysis method of a radio network is applied to a first-level NWDAF network element and includes: according to a to-be-performed first-class analysis, obtaining a second-level analysis report sent by a second-level NWDAF network element in correspondence with a network slice to which a target user equipment (UE) belongs; according to the second-level analysis report, sending a first-level analysis report to an NWDAF user, where the NWDAF user is configured to adjust network parameters of the first-class analysis according to the first-level analysis report.