CloudXR Subjective QoE Assessment over Mobile Networks Research

Hello everyone,

I am excited to share the outcomes of our latest research experiment using CloudXR 3.2. Our team evaluated the impact of various mobile network conditions (n=28)—round trip time (RTT), random jitter (RJ), packet loss (PL), and the combined effect of RTT and PL—on users’ (n=30) perceived Quality of Experience (QoE) while playing the first-person shooter game Serious Sam VR, streamed to an Oculus Quest 2 using CloudXR. You can read more about our findings in our recently published work [preprint-link]. Our results can help inform better decision-making under adverse network conditions from a QoE perspective.

Additionally, we have developed machine learning models that predict QoE based solely on these QoS factors. Using the dataset from our previous experiment, we propose three regression models, which we have shared with the community in our latest publication [preprint-link]. These models can be used as tools to learn in real-time how users perceive QoE, especially for latency-sensitive content such as first-person shooter games. Both of these works are currently under discussion in ITU-T SG12 standardization activities.

Please feel free to contact me by email (or post here) if you have any questions or would like to know more about our experiment results.

Thank you for sharing with the community!

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