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AI Connect: A Machine Learning based time series forecast for Wireless Network Optimization

The metrics associated with the health of wireless network systems are called KPIs or Key Performance Indicators. These are computed by arithmetic calculations done on counters or on the occurrences of specific alarms or certain keywords in the log files.

Wireless Network KPIs exhibit characteristics such as trends and seasonality – meaning they have an underlying structure and pattern based on time-of-day, day-of-the-week, month-of-the year etc.

This paper presents an approach to forecast Wireless Network KPIs using Time Series models. Such forecasts can provide valuable insights for executing critical network operations such as planning for hardware augmentation, swap-outs, fix-application, feature roll-out etc. It also helps being proactive in the network monitoring exercise, helping early prevention and detection of imminent issues.

 

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