From Theory to Practice: System QoE Assessment by Providers

Service and network providers actively evaluate and derive Quality of Experience (QoE) metrics within their systems, which necessitates suitable monitoring strategies. Objective QoE monitoring involves mapping Quality of Service (QoS) parameters into QoE scores, such as calculating Mean Opinion Scores (MOS) or Good-or-Better (GoB) ratios, by using appropriate mapping functions. Alternatively, individual QoE monitoring directly assesses user experience based on self-reported feedback. We discuss the strengths, weaknesses, opportunities, and threats of both approaches. Based on the collected data from individual or objective QoE monitoring, providers can calculate the QoE metrics across all users in the system, who are subjected to a range of varying QoS conditions. The aggregated QoE across all users in the system for a dedicated time frame is referred to as system QoE. Based on a comprehensive simulation study, the expected system QoE, the system GoB ratio, as well as QoE fairness across all users are computed. Our numerical results explore whether objective and individual QoE monitoring lead to similar conclusions. In our previous work [Hoss2024], we provided a theoretical framework and the mathematical derivation of the corresponding relationships between QoS and system QoE for both monitoring approaches. Here, the focus is on illustrating the key differences of individual and objective QoE monitoring and the consequences in practice.