Inactivity Timer Value Adjustment via NWDAF Analytics
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Solution Overview
Problem
In 5G networks, the existing methods for activating and deactivating PDU sessions incur significant control signaling overhead due to sub-optimal inactivity timer settings, which affects battery power consumption and network resource efficiency.
Innovation Solution
A method and apparatus using network analytics, specifically the Network Data Analytics Function (NWDAF), to dynamically set the inactivity timer value for PDU sessions based on communication description information and UE communications analytics, optimizing transitions between active and inactive states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If existing methods for activating and deactivating PDU sessions are used, then network operations can be maintained, but control signaling overhead increases and network resource efficiency decreases
Solution Approach 1:
The patent applies dynamics by making the inactivity timer value adjustable and adaptive rather than fixed. The timer value is dynamically modified based on network conditions, UE behavior patterns, and session characteristics, allowing the system to optimize between keeping sessions active (better resource efficiency) vs. deactivating them sooner (lower power consumption) based on real-time analytics
Solution Approach 2:
The core of the invention lies in changing the parameter of the inactivity timer value. By analyzing communication patterns, data volumes, session durations, and network conditions, the system determines optimal timer values to replace default settings, thereby reducing unnecessary session activations/deactivations that waste both power and network resources
2Productivity
If inactivity timer values are set to keep PDU sessions active longer, then network resource efficiency improves, but battery power consumption increases
Solution Approach 1:
The system changes the inactivity timer parameter based on multiple factors including UE communication behavior, data session characteristics, network load conditions, and historical patterns. This allows optimization of the timer value to balance between maintaining sessions active (improving resource efficiency) and avoiding excessive power consumption
Solution Approach 2:
The patent implements feedback mechanisms where the network analytics function continuously monitors session behavior, timer expiration events, and resource usage patterns. This feedback loop enables the system to learn from actual outcomes and adjust timer values accordingly, optimizing the trade-off between resource efficiency and power consumption over time
3Use of energy by moving object
If frequent PDU session activations and deactivations occur, then battery power consumption is reduced, but control signaling overhead increases
Solution Approach 1:
The system performs preliminary analysis of communication patterns and session characteristics before determining timer values. By predicting which sessions are likely to be active soon based on historical data and current patterns, the system can set longer timer values proactively, preventing unnecessary deactivations that would trigger activation/deactivation signaling overhead
Solution Approach 2:
The inactivity timer parameter is adjusted based on predicted session behavior patterns. For sessions identified as likely to remain active or reactivated soon, the timer is extended to avoid premature deactivation, thereby reducing the frequency of activation/deactivation cycles and associated signaling overhead
4Device complexity
If default inactivity timer settings are used, then system complexity is low, but network performance optimization is limited
Solution Approach 1:
The patent introduces a network analytics function as an intermediary between the default timer configuration and the actual timer application. This intermediary analyzes network data, UE behavior, and session characteristics to determine optimized timer values, achieving performance improvement without significantly increasing complexity at the UE or core network elements
Solution Approach 2:
The system implements self-service by having the network analytics function automatically monitor performance metrics, analyze patterns, and adjust timer values without manual intervention. This automation achieves continuous optimization while keeping operational complexity manageable through standardized analytics procedures
Data Source
AI summary
A method for setting a value of an inactivity timer for transitioning between states of a data session in a network comprising a first entity and a second entity providing network analytics is provided. The method includes obtaining, by the second entity, input data comprising communication description information for at least one user equipment (UE), and providing, by the second entity to the first entity, output analytics generated based on the input data, the output analytics comprising UE communications analytics for each data session where the output analytics are used to determining whether to update a value of an inactivity timer for a data session.