Cross-Domain Matrices for Radio-Core Network Failure Analysis
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Solution Overview
Problem
Existing network failure analysis systems are inefficient due to siloed expertise between radio and core networks, requiring specialized knowledge in both domains to diagnose failures, and are cumbersome in data handling and analysis.
Innovation Solution
Integrating radio network and core network failure analyses using cross-domain matrices, combined with weighted plots and integrated trace logs, to facilitate a comprehensive understanding of failed sessions by slicing and grouping data by location, frequency layers, and failure types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If separate analysis systems are used for radio network and core network failures, then specialized expertise in each domain is maintained, but the overall failure diagnosis becomes complex and requires multiple experts
Solution Approach 1:
The patent combines radio network failure data and core network failure data into a unified cross-domain matrix structure. This integration allows simultaneous analysis of both network domains in a single system, reducing the need for separate expert analyses while maintaining comprehensive diagnostic capability. The unified matrix correlates failures across domain boundaries, enabling holistic failure diagnosis.
Solution Approach 2:
The cross-domain matrix acts as an intermediary structure that bridges radio network and core network failure analyses. It provides a common framework that translates and correlates data from both domains, allowing insights from one domain to inform analysis in the other without requiring direct integration of complex specialized systems.
2Measurement precision
If comprehensive failure data from both radio and core networks is collected, then root cause identification accuracy improves, but data handling time and computational burden increase
Solution Approach 1:
The patent segments comprehensive failure data into distinct failure categories (radio network failures, core network failures, and cross-domain failures) organized in a matrix structure. This segmentation allows selective analysis of relevant failure types rather than processing all data uniformly, reducing computational burden while maintaining comprehensive coverage.
Solution Approach 2:
The patent transforms raw failure data into structured matrix parameters with specific attributes (failure type, domain, correlation strength). This parameter transformation enables efficient querying and analysis by converting unstructured comprehensive data into organized, searchable formats that reduce processing time.
3Loss of information
If detailed trace logs from both networks are integrated, then a complete view of failed sessions is achieved, but the complexity of analyzing the integrated data increases
Solution Approach 1:
The patent adds a cross-domain dimension to traditional single-domain failure analysis by creating a matrix that includes both radio network and core network perspectives. This dimensional expansion provides complete information coverage while organizing data in a structured format that manages complexity through systematic arrangement rather than chaotic integration.
Data Source
AI summary
The technology includes a system to integrate core and radio network failure analyses using cross-domain matrices. The system pulls core network trace logs from a core network and radio network trace logs from a radio network. The system creates a cross-domain trace log of failed sessions by matching the radio network trace logs with the core network trace logs. The system determines cross-domain matrices by assigning coordinates to the failure categories based on average user device signal strengths and average user device interference levels. The system generates plots of the cross-domain matrices and analysis recommendations for display to a user based on the cross-domain matrices.