Network Resource Model for gNB Split Functionality
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Solution Overview
Problem
Current network resource models, such as those used in LTE networks, are inadequate for supporting next generation node B (gNB) architectures, as they cannot effectively manage the split functionality between central and distributed units, leading to challenges in modeling and managing access nodes with distinct functional distributions.
Innovation Solution
The development of a network resource model that incorporates a gNB Function IOC, which contains Central Unit and Distributed Unit IOCs, allowing for flexible cardinalities and independent creation of gNB components, along with lifecycle management functions to instantiate network services containing virtual and physical network functions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If current network resource models (LTE models) are used, then existing network management is maintained, but they cannot effectively manage split functionality between central and distributed units of gNB
Solution Approach 1:
The patent segments the gNB into two distinct functional units: Central Unit (CU) and Distributed Unit (DU). Each unit is modeled as a separate network function with its own information object classes, allowing independent management and configuration. This segmentation enables the network resource model to handle the split functionality requirement while maintaining clear boundaries and management interfaces between units.
Solution Approach 2:
The patent creates a universal gNB function information object class that can represent both standalone gNBs and split gNBs. This universal model can instantiate either a single functional unit or multiple units (CU and/or DU) depending on deployment requirements, providing adaptability across different gNB architectures without requiring separate management models for each case.
2Adaptability or versatility
If gNB components are created independently with flexible cardinalities, then deployment flexibility is improved, but model complexity increases
Solution Approach 1:
The patent implements dynamic instantiation where the gNB function can adapt its structure at runtime based on deployment needs. The model allows the gNB to dynamically instantiate one or more CU instances and/or DU instances, with flexible cardinalities that can be adjusted without reconfiguring the entire system. This dynamic approach enables flexible deployment scenarios while the underlying model structure remains consistent.
Solution Approach 2:
The patent employs a nested model structure where the gNB function information object class contains nested information object classes for CU and DU units. This nesting allows the gNB to encapsulate multiple functional units within a single hierarchical structure, managing complexity through organized nesting rather than flat complexity, while still allowing independent creation and configuration of each unit.
3Extent of automation
If lifecycle management functions are added to instantiate network services, then service management capability is improved, but system complexity increases
Solution Approach 1:
The patent implements self-service capabilities through automated lifecycle management functions that can instantiate, configure, and manage network services without extensive manual intervention. The system includes automated service instantiation that can automatically create and configure gNB instances and their functional units based on service requirements, reducing operational complexity through automation while enhancing management capability.
Data Source
AI summary
Embodiments of the present disclosure describe methods and apparatuses for network resource modelling to support next generation node Bs.