A Neural Network for Quality of Experience Estimation in Mobile Communications
Laura Pierucci, Davide Micheli · IEEE Multimedia · 2016
High data rates are usually envisaged by operators to satisfy the subscribers using multimedia services. However, due to the increasing number of tablets, smartphones, and push applications, user needs can require low throughput. A new analysis of user satisfaction is necessary--the so-called quality of experience (QoE). The authors consider specific key performance indicators (KPIs) and propose using neural networks to provide an automatic classification among these KPIs (related to quality of service) and QoE. The adoption of the neural network ensures replicability of QoE estimation regardless of user involvement and simplifies QoE analysis for future communications systems.