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Mobile connectivity typically exhibits on-off behavior, i.e. phases of undisturbed data transmission are interrupted by outages. Recent matching efforts have shown that the durations of the onand off-phases can be matched by exponential distributions. The resulting exponential on-off models allow for elegant close-form solutions for performance metrics such as freeze probabilities in face of buffering, which amongst others allows for analysis-based interpretationsof the impacts of various keyparameters. Centering around exponential on-off behavior of mobile channels, this work provides a bridge between traffic measurements in mobile environments, closed-form traffic analysis based on Markov-modulated fluid flow models, and user perception of those kinds of disturbances that are typical for mobile environments. It also shows the need to focusQuality of Experience (QoE) studies on impact factors close to the source of the performance degradation, rather than on generic Quality of Service (QoS) parameters onpacket level.

Exponential On-Off Traffic Models for Quality of Experience and Quality of Service Assessment