An Intelligent Positioning and Prediction Method for 5G High Load Issues
With the rapid development and extensive deployment of 5G networks,the widespread adoption of 5G terminals in the market has led to an increasing burden on 5G networks.This burden is particularly prominent in high-density areas such as universities,commercial zones,and residential areas,where issues like delayed handling of high load problems and low analysis effi-ciency exist.This paper proposes an intelligent positioning and prediction method for addressing 5G high load issues.By leveraging the global,periodic,and real-time characteristics of Key Per-formance Indicators(KPIs),a load training model is constructed to monitor and analyze critical indicators.This allows for the rapid identification of changes in business scenarios and the pre-diction of load conditions for specific time frames or areas in the future.By precisely locating problematic cells before load issues occur,performing early prediction analysis,and intervening proactively,the approach preempts the network risks caused by business growth,thereby enhan-cing user perception.
5G high loadintelligent positioning predictionbusiness scenario recognitionPer-ception depressive inflection point
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