Core Network RAT Detection for NSA Mobility and Charging
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Solution Overview
Problem
In 5G Non-Standalone (NSA) Option 3 deployment, the core network cannot determine the Radio Access Technology (RAT) type used by User Equipment (UE) at any point in time during an IP-CAN session, leading to challenges in differentiated charging and user plane traffic optimization.
Innovation Solution
A method where the Gateway Control plane (GW-C) node selects a Gateway User plane (GW-U) node capable of handling dual connectivity based on the RAT type, using reinforcement learning or RAN exposure to insert RAT type in IP data packets, enabling tailored mobility operations and enforcement actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the core network uses a unified charging and management approach for all users, then the system complexity is reduced and ease of operation is improved, but the ability to provide differentiated services and optimized charging based on actual RAT type is lost
Solution Approach 1:
The patent segments the charging and management approach by RAT type. The PCRF node retrieves and applies different PCC rules based on whether the UE is connected via LTE or NR, enabling differentiated service handling while maintaining a unified core network architecture. This segmentation allows tailored charging, QoS, and traffic optimization for each RAT type.
Solution Approach 2:
The system performs preliminary action by pre-configuring different PCC rules in the PCRF node for different RAT types before actual data transmission. When a UE establishes an IP-CAN session, the PCRF already has the appropriate rules ready to apply based on the RAT type indication received from the SGW-C/PGW-C node, enabling immediate differentiated handling without real-time complexity.
2Measurement precision
If the core network implements RAT-type-specific charging and optimization, then service differentiation and charging accuracy are improved, but the device complexity and information processing requirements increase
Solution Approach 1:
The patent introduces an intermediary mechanism where the SGW-C/PGW-C node acts as a mediator between the RAN and PCRF. This node receives the RAT type indication from the access network and forwards it to the PCRF, which then applies the appropriate PCC rules. This intermediary approach distributes the complexity across multiple nodes rather than concentrating it in one location, reducing overall system complexity while maintaining precise RAT type detection.
Solution Approach 2:
The PCRF node is designed with multi-functionality to handle both unified and differentiated charging scenarios. It can retrieve and apply generic PCC rules for all users or RAT-type-specific rules when needed, making the node adaptable to different operational modes without requiring separate dedicated systems for each function.
3Ease of manufacture
If the network uses generic PCC rules for all users, then the ease of manufacture and deployment is improved, but the ability to optimize user plane traffic based on actual RAT characteristics is reduced
Solution Approach 1:
The patent implements a dynamic rule selection mechanism in the PCRF node. Instead of using static generic rules for all users, the system dynamically retrieves and applies RAT-type-specific PCC rules based on the actual RAT type indication received for each UE. This dynamic adaptation enables optimized user plane traffic handling for LTE and NR while maintaining a unified deployment architecture that doesn't require separate network configurations.
Data Source
AI summary
A method of enabling the core network to determine the RAT type in a dual connection non-standalone configuration. The RAT type is either embedded in the GTP-U header by the RAN which is then extracted by the PGW-U or it is derived by the PGW-U by using a Reinforcement Language Agent activated by the SPR, through the PCRF and the PGW-C.