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Forecasting the capacity of mobile networks

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  • João A. Bastos

    (Nokia)

Abstract

The optimization of mobile network capacity usage is an essential operation to promote positive returns on network investments, prevent capacity bottlenecks, and deliver good end user experience. This study examines the performance of several statistical models to predict voice and data traffic in a mobile network. While no method dominates the others across all time series and prediction horizons, exponential smoothing and ARIMA models are good alternatives to forecast both voice and data traffic. This analysis shows that network managers have at their disposal a set of statistical tools to plan future capacity upgrades with the most effective solution, while optimizing their investment and maintaining good network quality.

Suggested Citation

  • João A. Bastos, 2019. "Forecasting the capacity of mobile networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 72(2), pages 231-242, October.
    • Handle: RePEc:spr:telsys:v:72:y:2019:i:2:d:10.1007_s11235-019-00556-w
    DOI: 10.1007/s11235-019-00556-w
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    Cited by:

    1. Irina Kochetkova & Anna Kushchazli & Sofia Burtseva & Andrey Gorshenin, 2023. "Short-Term Mobile Network Traffic Forecasting Using Seasonal ARIMA and Holt-Winters Models," Future Internet, MDPI, vol. 15(9), pages 1-15, August.

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    More about this item

    Keywords

    Mobile networks; Forecasting practice; ARIMA models; Exponential smoothing; Time series;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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