Cell State Prediction in Radio Access Networks
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Solution Overview
Problem
Current methods are unable to predict when a cell in a radio access network (RAN) will enter a sleeping state, leading to delayed detection and resulting in poor network performance, revenue loss, and increased operating expenses.
Innovation Solution
A method and system for predicting a cell's state in a RAN by obtaining cell information, determining sets of conditions indicating a decrease in Random Access Channel (RACH) success rate, and predicting the cell will enter a sleeping state when these conditions are met.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional detection methods are used to identify sleeping cells, then detection is simple, but detection delay is long (24-48 hours)
Solution Approach 1:
The system performs preliminary actions by continuously monitoring cell performance parameters and calculating probabilities of cells entering sleeping state before the actual state transition occurs. This allows early detection and preventive measures to be taken, reducing the detection delay from 24-48 hours to a much shorter timeframe while maintaining manageable system complexity through automated algorithms.
Solution Approach 2:
The system implements feedback mechanisms by continuously collecting cell performance data, analyzing trends, and adjusting predictions based on historical patterns. The feedback loop processes performance parameters, calculates sleeping state probabilities, and triggers alerts or preventive actions when thresholds are met, enabling timely detection without requiring overly complex manual monitoring systems.
2Reliability
If no prediction method is implemented, then system operation is simple, but network performance deteriorates due to undetected sleeping cells
Solution Approach 1:
The patent replaces manual monitoring and reactive repair mechanisms with an automated prediction system that uses algorithms to analyze performance parameters and calculate sleeping state probabilities. This substitution improves network reliability by enabling proactive detection while keeping the system complexity manageable through automated decision-making processes rather than human intervention.
Solution Approach 2:
The prediction system performs self-service by automatically collecting data, analyzing trends, generating predictions, and triggering alerts without requiring continuous human oversight. The system uses historical performance data to train models and improve predictions over time, enhancing network reliability while maintaining operational simplicity through automation.
3Loss of information
If early detection of sleeping cells is achieved, then revenue loss is reduced, but measurement and detection difficulty increases
Solution Approach 1:
The system uses a universal approach by monitoring multiple performance parameters (RACH success rate, handover success rate, throughput, etc.) simultaneously to detect sleeping cells. This multi-functional monitoring framework reduces revenue loss by detecting various indicators of cell degradation while managing detection complexity through integrated analysis of all parameters rather than separate specialized systems.
Solution Approach 2:
The system detects sleeping cells by monitoring changes in performance parameters over time, such as declining RACH success rates or throughput degradation. By tracking parameter trends and calculating probability thresholds, the system achieves early detection that prevents revenue loss while managing measurement difficulty through automated parameter analysis rather than manual inspection.
Data Source
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AI summary
A method and system for predicting a state of a cell (11) in a radio access network are described herein. The method comprises obtaining (S210) information of the cell (11), determining (S220) one or more sets of conditions based on the information and predicting (S230) that the cell (11) will enter a sleeping state when at least one set of the one or more sets of conditions is fulfilled. The method further comprises outputting (S240) an action to prevent the cell (11) from entering the sleeping state based on the probability and a number of wireless devices currently connected to the cell (11).