Cell Correlation Analysis for Silent 5G Base Station Failure Prediction
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Solution Overview
Problem
Existing techniques for predicting failures in radio communication systems, particularly in 5G networks, suffer from insufficient accuracy, especially in detecting silent failures that do not immediately affect service quality but can degrade user experience over time.
Innovation Solution
A failure prediction apparatus and method that utilizes correlation coefficient data to analyze communication states of cells and base stations, employing AI models to determine the state of a target cell or base station by calculating correlations with reference cells and communication areas, and generating feature amounts to predict potential failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional failure prediction techniques are used, then the system structure is simple, but the prediction accuracy is insufficient
Solution Approach 1:
The system segments the radio communication network into multiple cells, each with its own communication state data. By analyzing each cell individually and comparing it with reference cells, the system can detect subtle failures that would be missed in a holistic approach, thereby improving prediction accuracy without overwhelming complexity
Solution Approach 2:
The patent introduces correlation coefficient data as an intermediary metric between communication state data and failure prediction. This intermediary transforms complex communication state information into a measurable similarity metric, enabling accurate failure detection while maintaining system manageability through standardized calculation procedures
2Reliability
If monitoring of communication state data is increased, then failure detection capability improves, but processing load increases
Solution Approach 1:
The system applies local quality analysis by focusing correlation coefficient calculations on specific cells that show abnormal patterns. Rather than uniformly processing all cell data, the system identifies and deep-dives into problematic local areas, improving detection capability while reducing overall processing load through targeted analysis
Solution Approach 2:
The patent performs preliminary actions by pre-identifying reference cells and pre-calculating correlation thresholds. This preparation allows the system to efficiently detect failures during operation without performing computationally intensive analyses in real-time, thus improving reliability while controlling processing load
Data Source
AI summary
A non-transitory computer-readable storage medium storing therein a failure prediction program for causing a computer to execute a process includes, generating at least one of first correlation coefficient data representing a similarity between first communication state data representing a communication state of a first cell provided by a first base station and second communication state data representing a communication state of a second cell provided by a second base station, or second correlation coefficient data representing a similarity between the first communication state data and third communication state data representing a communication state in a communication area of the first base station, and determining a state of the first base station or the first cell on the basis of at least one of the first correlation coefficient data or the second correlation coefficient data.