Mobile Network Anomaly Diagnosis via Control Plane Message Analysis
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Solution Overview
Problem
Conventional methods for diagnosing anomalies in mobile network control planes struggle to detect unnoticeable issues and accurately determine their causes, often leading to unintended problems due to the complexity of standards and variations in network implementations among mobile network operators.
Innovation Solution
A network anomaly diagnosis device that includes a data analyzer to receive and analyze control plane messages from multiple mobile network operators, a database to store and compare analysis results, and a controller to identify anomalies by comparing procedure orders and times across different networks, facilitating the detection of unnecessary procedures and timing mismatches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional anomaly diagnosis methods using simple statistics values are used, then the diagnosis process is simple, but the ability to discover unnoticeable problem phenomena and accurately ascertain causes is insufficient
Solution Approach 1:
The patent segments control plane messages into detailed procedural steps and divides the analysis into multiple dimensions including procedure order, execution time, and frequency. This segmentation enables precise identification of anomaly causes while maintaining systematic analysis through structured breakdown of message components.
Solution Approach 2:
The patent introduces multiple analysis dimensions beyond simple statistics, including temporal dimension (procedure execution time), sequential dimension (procedure order), and frequency dimension. This multi-dimensional approach transforms one-dimensional statistical analysis into comprehensive multi-dimensional diagnostic capability.
2Measurement precision
If detailed analysis of control plane messages is performed to accurately diagnose anomalies, then the diagnostic accuracy improves, but the complexity of the diagnosis system increases
Solution Approach 1:
The server performs multiple functions including message collection, detailed analysis, statistical processing, and anomaly diagnosis using a single integrated system. This multi-functional approach enables comprehensive diagnostic capability without requiring separate specialized systems for each function.
Solution Approach 2:
The system automatically collects control plane messages from multiple mobile networks, performs detailed procedural analysis, and generates diagnostic reports without manual intervention. This self-service capability reduces operational complexity while maintaining high diagnostic accuracy through automated multi-dimensional analysis.
3Reliability
If control plane messages from multiple mobile networks are collected and compared, then the ability to identify fundamental anomalies improves, but the amount of data to be processed increases
Solution Approach 1:
The system extracts only the essential procedural information from control plane messages, focusing on procedure order, execution time, and frequency. This extraction approach filters out redundant data while retaining critical diagnostic information, enabling reliable multi-network comparison without processing unnecessary data volume.
Solution Approach 2:
The patent transforms raw control plane message data into standardized parameters including procedure execution time, occurrence frequency, and sequence order. This parameter transformation enables efficient comparison across multiple networks by converting diverse message formats into uniform analytical parameters.
Data Source
AI summary
A network anomaly diagnosis device and a method thereof are provided. The network anomaly diagnosis device includes a data analyzer configured to receive a control plane message for a service provided to a terminal by a mobile network operator (MNO) from the terminal and analyze the control plane message, a database configured to collect results of analyzing control plane messages for services provided to the terminal by different MNOs including the MNO from the data analyzer and store the result of analyzing the control plane message for each MNO, and a controller configured to compare the result of analyzing the control plane message of the MNO at the data analyzer with the result of analyzing the control plane message for each MNO, the result being stored in the database.