Dynamic Data Rate Adjustment for Wireless Network Slices
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Solution Overview
Problem
Current wireless communication systems lack a technique to dynamically adjust data rate limits for user equipment (UE) operating within a network slice, leading to inefficient resource management and potential network congestion.
Innovation Solution
A network node equipped with processor circuitry performs a network slice quota management (NSQ) function, which involves counting the number of UEs and protocol data unit (PDU) sessions in a network slice, and dynamically adjusts the data rate limit of UEs based on predetermined limitations to ensure fair resource distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If data rate limits are statically configured for UEs in network slices, then network resource management is simplified, but resource utilization efficiency deteriorates and network congestion occurs
Solution Approach 1:
The patent implements dynamic data rate adjustment by continuously monitoring the number of UEs and PDU sessions in each network slice and adjusting data rate limits in real-time based on current network conditions, transforming the static configuration into a dynamic adaptation mechanism that optimizes resource utilization while maintaining manageable complexity
Solution Approach 2:
The system establishes a feedback loop where the network node continuously counts UEs and PDU sessions, compares actual data rate consumption against allocated limits, and adjusts data rate limits accordingly. This closed-loop control mechanism enables automatic optimization of network resources based on real-time slice utilization metrics
2Productivity
If data rate limits are dynamically adjusted for each UE in network slices, then network resource utilization efficiency is improved, but system complexity increases
Solution Approach 1:
The network node is enhanced with multi-functional capabilities to perform counting of UEs and PDU sessions, calculation of data rate limits, and dynamic adjustment operations within a single integrated system. This universal approach consolidates multiple functions into one node, improving resource utilization while managing complexity through functional integration rather than distribution
Solution Approach 2:
The system dynamically changes key parameters including the number of monitored UEs, count of PDU sessions, and data rate limit values based on network conditions. By making these parameters adaptive rather than fixed, the system achieves high resource utilization efficiency while the parameter adjustment logic remains centralized and manageable
3Productivity
If higher data rate limits are allocated to UEs in network slices, then network performance is improved, but network congestion and resource exhaustion occur
Solution Approach 1:
The patent allocates data rate limits that are partially excessive relative to immediate needs, allowing UEs to achieve high performance when slice utilization is low, while implementing corrective reduction when utilization approaches capacity thresholds. This partial over-allocation strategy enables performance optimization while preventing complete resource exhaustion through dynamic correction
Solution Approach 2:
The system uses feedback from UE and PDU session counting to continuously monitor slice utilization and adjust data rate limits accordingly. When the number of UEs or sessions indicates approaching capacity, the feedback mechanism triggers data rate reduction to prevent congestion, thereby maintaining both high performance and network reliability through adaptive control
Data Source
AI summary
Several techniques using a network slice quota (NSQ) management function provide dynamic adjustment in order to meet the limitation of data rate per network slice in the uplink and downlink wireless connections in a wireless network. In one technique, when the limit is reached, the session aggregated maximum bit rates (AMBR) per subscription level is adjusted in proportionate ratio of the maximum bit rate per subscription level per user equipment (UE). In another technique, when the limit is reached, there is a proportionate equivalent increment and decrement of session AMBR based on usage patterns of the subscription levels. In a further technique, when the limit is reached, there is a proportionate equivalent increment and decrement of slice resources based on usage patterns. In yet another technique, a quota update is attempted using the Unified Data Repository (UDR).