Network Problem Analysis With User KPI Impact Quantification
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Solution Overview
Problem
Current network problem analysis in telecommunication networks lacks accuracy due to high uncertainty in alarm occurrence and user service behavior, leading to unreliable quantification of impact on key performance indicators (KPIs).
Innovation Solution
A method that integrates network problem data with user data to generate a comprehensive network problem analysis result, including confidence levels and deterioration degrees of KPIs, by identifying abnormal network elements and users affected by the problem, utilizing standardized data and network topology analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If network problems are compressed or filtered based on co-existence analysis to reduce processing quantity, then productivity is improved, but measurement precision of impact degree deteriorates
Solution Approach 1:
The patent introduces user data information as an intermediary element to bridge network problem data and KPI analysis. By obtaining user data information including KPIs and establishing correlation relationships between network problems and user services, the system achieves both efficient processing and accurate impact quantification. The user data serves as a mediator that enables precise measurement without requiring processing of all network problems individually.
2Device complexity
If analysis is performed based only on co-existence degree of user data, then device complexity is reduced, but measurement precision of impact degree deteriorates due to fluctuation impact
Solution Approach 1:
The patent segments the analysis process into distinct modules: obtaining network problem data information, obtaining user data information, determining correlation relationships, and generating analysis results. This segmentation allows the system to handle complex relationships systematically while maintaining manageable complexity. Each module processes specific data types and produces intermediate results that feed into the final analysis, improving both precision and implementability.
3Productivity
If network problem analysis focuses on timeliness of handling, then productivity is improved, but measurement precision of analysis result deteriorates due to random alarm occurrence
Solution Approach 1:
The patent implements feedback mechanisms by continuously monitoring user KPIs and comparing them against baseline values to determine impact degrees. The system uses correlation relationships between network problems and user services to provide feedback on actual impact, allowing for timely handling while maintaining accuracy. The feedback loop enables the system to adjust analysis results based on real-time data, resolving the contradiction between speed and precision.
Data Source
AI summary
A method includes obtaining network problem data information, where the network problem data information indicates a network problem that occurs on a network element in a first network; obtaining user data information, where the user data information is user data information of at least one user served by the first network, and the user data information includes a key performance indicator (KPI) of the user; and generating a network problem analysis result based on the network problem data information and the user data information, where the network problem analysis result indicates an impact degree of the network problem on the KPI.