MDA Analytics Reports for SON Coverage Issue Diagnosis
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Solution Overview
Problem
The increasing flexibility of 5G networks to support diverse communication services presents operational and management challenges, with unclear specifications for Management Data Analytics (MDA) on how and what Management Data Analytics Services (MDAS) are provided and consumed, leading to inefficiencies in diagnosing network issues, predicting potential failures, and optimizing network resources.
Innovation Solution
Implementing Management Data Analytics (MDA) with AI and ML techniques to analyze network data, providing analytics reports for root cause analysis, preventative actions, and optimizing network resources, and integrating with Self-Organizing Networks (SON) for automated management and orchestration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If 5G networks support diverse communication services with increasing flexibility, then service capability and adaptability are improved, but operational and management complexity increases
Solution Approach 1:
The system implements self-service through automated anomaly detection, root cause analysis, and resolution recommendation generation. The MDA system automatically monitors network performance, identifies coverage holes and interference spots, analyzes their causes, and provides remediation recommendations without requiring manual intervention for each issue.
Solution Approach 2:
The patent replaces manual mechanical analysis processes with automated data analytics systems. Machine learning models and algorithms substitute human operators in analyzing network data, identifying anomalies, and determining root causes, thereby reducing management complexity while maintaining service flexibility.
2Productivity
If current Management Data Analytics systems are used, then basic network monitoring is performed, but effective diagnosis and prevention of network issues like coverage holes and interference spots is not achieved
Solution Approach 1:
The system implements comprehensive feedback mechanisms by continuously monitoring network performance metrics, comparing them against baseline thresholds, and automatically triggering anomaly detection and root cause analysis when deviations are detected. This closed-loop feedback enables effective diagnosis and prevention of network issues.
Solution Approach 2:
The MDA system performs preliminary actions by proactively identifying potential coverage holes and interference spots before they significantly impact service quality. The system uses predictive analytics to detect emerging issues and generates prevention recommendations in advance, allowing operators to address problems before they degrade network performance.
Data Source
AI summary
Disclosed embodiments are related to Management Data Analytics (MDA) relation with Self-Organizing Network (SON) functions and coverage issues analysis use case. An MDA Service (MDAS) obtains input data related to one or more managed networks and services from one or more data sources; generates an analytics report based on analysis of the input data; and sends an analytics report to a Self-Organizing Network (SON) function for root cause analysis of ongoing issues, prevention of potential issues, and/or prediction of network or service demands. The analytics report may describe an identified network or cell coverage issue related to the SON function. Other embodiments may be described and/or claimed.