5G Slice Performance Measurement Through PCF-UPF Log Correlation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The lack of a comprehensive performance measurement framework for 5G slicing hinders telecommunications operators from guaranteeing promised service levels, leading to customer dissatisfaction and operational inefficiencies due to limited visibility into network slice utilization and resource allocation.
Innovation Solution
Deriving insights from signaling transaction logs of the PCF and UPF in 5G SA Core Platforms to cross-map data using timestamp information, enabling the identification of key performance indicators (KPIs) for network slices and dynamic resource reallocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If operators implement 5G slicing for customized services, then service differentiation and subscriber satisfaction improve, but the complexity of performance measurement and resource management increases
Solution Approach 1:
The patent introduces an intermediary system that correlates PCF policy data with UPF traffic data to measure 5G slicing performance. This intermediary correlation mechanism bridges the gap between policy enforcement and actual traffic handling, enabling performance measurement without requiring direct modifications to the core network elements.
Solution Approach 2:
The patent replaces complex manual performance measurement mechanisms with automated data correlation using timestamp-based matching. Instead of manual monitoring and analysis, the system automatically correlates policy and traffic data through timestamp alignment, substituting mechanical measurement processes with automated computational methods.
2Ease of operation
If operators lack performance measurement framework, then operational simplicity is maintained, but service level guarantee and customer satisfaction deteriorate
Solution Approach 1:
The patent enables the network to self-measure its own performance by automatically correlating PCF and UPF data. The system performs self-diagnosis and self-monitoring of slicing performance without requiring external measurement tools or complex manual intervention, maintaining operational simplicity while ensuring service level guarantees.
Solution Approach 2:
The patent implements a feedback mechanism where performance data derived from correlating PCF and UPF logs provides insights back to the network operators. This feedback loop enables continuous monitoring and improvement of service levels, allowing operators to respond to performance issues and guarantee service quality.
3Loss of information
If operators implement comprehensive performance monitoring, then visibility into network slice utilization improves, but data processing complexity and resource consumption increase
Solution Approach 1:
The patent extracts only the essential data elements needed for performance measurement from the PCF and UPF logs - specifically timestamp, slice identifier, and relevant performance metrics. By extracting only the necessary information rather than processing complete log files, the system reduces data processing complexity while maintaining comprehensive visibility into network slice utilization.
Solution Approach 2:
The patent segments the performance measurement process into distinct components: PCF data extraction, UPF data extraction, timestamp-based correlation, and KPI calculation. This segmentation allows each component to be processed independently and efficiently, reducing overall data processing complexity while achieving comprehensive monitoring capability.
Data Source
AI summary
Systems and methods are provided for deriving insights of customer key performance indicators (KPI's) (e.g., throughput, latency, connection reliability, etc.) in 5G slicing. By using signaling transaction logs from 5G SA Core Platforms, such as the PCF and UPF, full visibility can be provided to ensure customer satisfaction. The data on these KPIs can allow the mobile operator to derive the subscriber's experience metrics based on their specific location to make real-time dynamic changes based on this visibility data.