RET Label Association Using KPI Feedback in SON Networks
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Solution Overview
Problem
Incorrect or missing Remote Electrical Tilt (RET) labels in wireless telecommunication networks lead to inefficient network performance, as manual updates are time-consuming and prone to errors, and existing automated systems lack effective means to verify label accuracy, resulting in resource waste and suboptimal network adjustments.
Innovation Solution
Implement a central controller that collects and analyzes Key Performance Indicators (KPIs) to identify significant changes in network metrics, uses digital twinning for simulation, and applies algorithms to correct RET labels, ensuring accurate associations between cells and RETs, thereby optimizing antenna tilts for improved coverage and reduced interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual updates of RET labels are performed, then RET labels can be updated, but the process is time-consuming and prone to errors
Solution Approach 1:
The system automatically detects and corrects RET label errors using network performance data without requiring manual intervention. The central controller autonomously analyzes KPI changes, identifies mislabeled RETs, and corrects associations, enabling the system to self-diagnose and self-repair labeling errors.
Solution Approach 2:
The system uses network performance feedback (KPI changes) to verify RET label accuracy. By monitoring whether expected performance improvements occur after RET adjustments, the system detects labeling errors and triggers automatic correction, creating a closed-loop verification mechanism.
2Productivity
If automated systems are used to update RET labels, then update speed increases, but verification of label accuracy is lacking
Solution Approach 1:
The system implements a feedback mechanism that monitors network performance metrics (KPIs) to verify whether RET label corrections are accurate. By comparing actual performance changes against expected outcomes, the system validates label accuracy automatically.
Solution Approach 2:
The patent replaces manual verification processes with automated algorithmic verification using network performance data. Instead of human engineers checking labels, the system uses computational analysis of KPI changes to verify label accuracy, substituting mechanical/manual verification with automated digital verification.
3Loss of energy
If incorrect RET labels are not corrected, then network resources are wasted, but manual detection is inefficient
Solution Approach 1:
The system uses network performance feedback to automatically detect mislabeled RETs. By monitoring whether RET adjustments produce expected performance improvements, the system identifies labeling errors without requiring complex external detection infrastructure.
Solution Approach 2:
The system performs self-detection of labeling errors using its own network performance monitoring capabilities. The central controller autonomously analyzes KPI data to identify mislabeled RETs, eliminating the need for separate manual detection processes.
Data Source
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AI summary
Methods for configuring a self-organizing network (SON) of a cellular telecommunication network are disclosed. A first set of data comprised of substantially real-time data for one or more key performance indicators (KPIs) is collected. A characteristic profile of the KPIs is determined. An instruction is sent to an identifier associated with the selected adjustable antenna, indicative of a command to change an electromagnetic characteristic of the selected adjustable antenna. A second set of data for the KPIs is received, and an updated profile of the KPIs is determined. A statistical probability of a causal relationship between the updated profile and the change to the electromagnetic is determined based on a predetermined threshold. Identifiers for the adjustable antennas are updated or confirmed.