Mobile Network Synchronization Anomaly Correlation for Root Cause Analysis

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Solution Overview

Problem

Existing mobile network monitoring systems struggle to effectively detect and correlate synchronization domain anomalies across multiple domains, leading to a lack of understanding of their impact on network services and an inability to identify root causes.

Innovation Solution

An automated anomaly detection and correlation system that integrates multiprotocol testing devices, active test probes, and machine learning to analyze synchronization domain performance data alongside other network domains, identifying anomalies, correlating them, and determining root causes and remedial actions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional synchronization monitoring systems are used, then individual clock performance can be monitored, but there is no insight or combination with data from other network domains

Engineering Contradiction:

Improvesynchronization performance monitoringVSAvoidimpact understanding on network services

Core Design Contradiction:

Measurement precisionVSLoss of information

Solution Approach 1:

The patent combines synchronization domain monitoring with other network domains (transport, core, RAN) into a unified monitoring system. The system collects and correlates data from multiple domains simultaneously, merging previously separate monitoring functions into an integrated solution that provides comprehensive network visibility.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The monitoring system is designed to perform multiple functions across different network domains. It can monitor synchronization performance, transport network status, core network operations, and RAN performance within a single platform, making the system universal rather than domain-specific.

Inventive Principle:

Principle #6Universality (Multi-functionality)

2Reliability

If multiple network domains are monitored separately, then domain-specific anomalies can be detected, but root cause identification across domains remains difficult

Engineering Contradiction:

Improveanomaly detection accuracyVSAvoidcross-domain correlation complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent introduces an intermediary correlation engine that acts as a mediator between multiple domain-specific monitoring systems. This intermediary component receives data from various domains, performs automated correlation analysis, and identifies root causes without requiring complex direct integration between all domain systems.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system implements feedback mechanisms where anomaly detection results from one domain are fed back into the correlation engine, which then adjusts monitoring priorities and resource allocation. This feedback loop enables dynamic adaptation to changing network conditions and simplifies cross-domain analysis.

Inventive Principle:

Principle #23Feedback

3Ease of operation

If manual investigation of network anomalies is performed, then skilled operators can analyze data, but the process is time-consuming and difficult even for experts

Engineering Contradiction:

Improveanomaly investigation capabilityVSAvoidinvestigation time

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

The monitoring system performs self-service through automated anomaly detection and root cause identification algorithms. The system automatically analyzes data, detects anomalies, correlates events across domains, and identifies root causes without requiring manual operator intervention for each incident, thereby reducing both time loss and operational complexity.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical analysis processes with automated computational systems. Machine learning algorithms and automated correlation engines substitute for human operators in detecting and analyzing anomalies, significantly reducing investigation time while maintaining or improving accuracy.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS12537735B2Mobile network synchronization domain anomaly identification and correlation

Publication Date: 2026.01.27 TC FRANCE SAS

AI summary

Systems and methods of mobile network synchronization domain anomaly identification and correlation include receiving measurements from a synchronization domain reflecting the performance of synchronization across a mobile network; identifying synchronization domain anomalies in the measurements from the synchronization domain; correlating of the synchronization domain anomalies against anomalies from other domains of the mobile network; and one or more of (1) identifying root causes of the synchronization domain anomalies and the anomalies from other domains, (2) identifying associated impact on services and/or subscribers of the synchronization domain anomalies and the anomalies from other domains, and (3) identifying remedial actions for the synchronization domain anomalies and the anomalies from other domains.