Smartphones have become increasingly prevalent and important in our daily lives. To meet users' expectations about the Quality of Experience (QoE) of mobile applications (apps), it is essential to obtain a comprehensive understanding of app QoE and identify the critical factors that affect it. However, effectively and systematically studying the QoE of popular mobile apps such as Facebook and YouTube still remains a challenging task, largely due to a lack of a controlled and reproducible measurement methodology, and limited insight into the complex multi-layer dynamics of the system and network stacks.

To conserve power while ensuring good performance on resource-constrained mobile devices, devices transition between different Radio Resource Control (RRC) states in response to network traffic and according to parameters specific to network operators. As RRC states significantly affect application power consumption and performance, it is important to understand how RRC state timers interact with network traffic patterns. In this paper, we show that the impact of RRC states on performance is significantly more complex and diverse than found in previous work. To do so, we introduce an open-source tool that allows the impact of RRC states on network and application performance to be measured in a robust and accurate manner on unmodified user devices, and deploy the tool in 23 countries around the world to test a broad range of cellular network technologies. We detect previously unknown performance problems which increase network latencies by up to several seconds and for LTE, can increase packet losses by an order of magnitude. Through an in-depth cross-layer analysis of several carriers, we examine the lower-layer causes of these problems. We determine that the highly complex state transitions of certain carriers, and in particular poor interactions between state demotions and network traffic, can lead to substantial, unexpected latencies.