Correlating User and Control Plane Data for Soft Drop Detection
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Solution Overview
Problem
Current network management systems struggle to detect 'soft drops' in communication networks, where users intentionally terminate sessions due to service quality issues, as these events are masked by normal session terminations and not explicitly reported by control plane protocols.
Innovation Solution
A method that correlates user plane and control plane information to identify soft drops, using media Quality of Service parameters and signaling procedures, and an anomaly detection module to learn normal patterns and predict service quality issues, thereby detecting hidden problems that affect customer experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional fault management and performance monitoring systems are used, then network failures and basic service issues can be detected, but service quality issues that do not generate explicit alarms remain hidden
Solution Approach 1:
The patent introduces an intermediary analysis layer that correlates control plane signaling data with user plane quality metrics. This intermediary system detects soft drops by finding correlations between signaling success codes and user plane quality degradation, thereby revealing hidden service quality issues that traditional monitoring systems miss.
2Productivity
If control plane protocols are monitored, then session termination events can be detected, but intentional terminations due to service quality issues cannot be distinguished from normal terminations
Solution Approach 1:
The system implements feedback by continuously monitoring user plane quality metrics and comparing them against session termination events. When quality degradation is detected prior to termination, the system feeds this information back to classify the termination as a soft drop, thereby improving measurement precision without reducing monitoring efficiency.
Solution Approach 2:
The patent adds another dimension of analysis by incorporating user plane quality metrics (packet loss, jitter, throughput) alongside control plane signaling data. This multi-dimensional approach enables differentiation between normal and quality-related terminations, improving detection accuracy while maintaining efficient session monitoring.
3Productivity
If performance monitoring counters are used, then basic network performance can be tracked, but service quality issues affecting specific user subsets are hidden due to averaging
Solution Approach 1:
The patent segments the network monitoring data by user equipment, service type, and network slice. This segmentation allows the system to track performance metrics for specific user subsets separately, preventing averaging from masking localized service quality issues while maintaining overall network-wide performance tracking efficiency.
Data Source
AI summary
A method for monitoring a communication network comprises monitoring user plane information and control plane information for a first session provided by the communication network for a first wireless device; and correlating the user plane information and the control plane information to determine if the first session was ended due to a soft drop, wherein a soft drop corresponds to a user of the wireless device intentionally terminating the first session due to service quality issues.