Monitoring the Quality of Experience (QoE) of the customer base is a key task for Mobile Network Operators (MNOs), and it is generally performed by collecting users feedbacks through directed surveys. When such feedbacks are few in number, a MNO may predict the users QoE starting from objective network measurements, gathered directly from the users equipments through crowdsourcing. In this work, we compare such a traditional approach with a different one, where the data used for predicting the users QoE is gathered directly at the network access, using Key Performance Indicators (KPI) available on each base station. Although such KPIs are aggregated by design (i.e., they refer to the distribution of a population of users rather than to a single individual), we show through experiments with a country-wide dataset that their predictive power is comparable and in some cases superior than the one of crowdsourcing. Such a result is particularly attractive for MNOs, since network KPIs are generally much easily obtainable than crowdsourcing data.

Crowdsourcing or Network KPIs? A Twofold Perspective for QoE Prediction in Cellular Networks

Pimpinella, Andrea;Redondi, Alessandro Enrico Cesare
2021-01-01

Abstract

Monitoring the Quality of Experience (QoE) of the customer base is a key task for Mobile Network Operators (MNOs), and it is generally performed by collecting users feedbacks through directed surveys. When such feedbacks are few in number, a MNO may predict the users QoE starting from objective network measurements, gathered directly from the users equipments through crowdsourcing. In this work, we compare such a traditional approach with a different one, where the data used for predicting the users QoE is gathered directly at the network access, using Key Performance Indicators (KPI) available on each base station. Although such KPIs are aggregated by design (i.e., they refer to the distribution of a population of users rather than to a single individual), we show through experiments with a country-wide dataset that their predictive power is comparable and in some cases superior than the one of crowdsourcing. Such a result is particularly attractive for MNOs, since network KPIs are generally much easily obtainable than crowdsourcing data.
2021
2021 IEEE Wireless Communications and Networking Conference (WCNC)
978-1-7281-9505-6
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1176632
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