A Demonstration of QoE Assessment for Cloud-based Social XR Applications over Mobile Networks

Cloud-based social eXtended Reality (XR) services are the cornerstone for realizing the promises of the Metaverse. These services hosted either on datacenters or edge, will demand stringent mobile network quality of service (QoS) to operate effectively and provide an acceptable user quality. It becomes fundamental to study how mobile networks QoS factors round-trip time (RTT), packet loss (PL), and jitter affect these services by measuring their effect on users' perceived quality of experience (QoE). Subjective QoE assessment involves carefully controlled laboratory environments to generate the desired conditions between a large set of users. The requirements for a cloud-based social XR service lab-setup are complex: Identify a reliable streaming service, a customizable VR application, emulate network conditions, define activities or tasks for users to perform, collect their data, label it; all while mitigating possible human mistakes. To address these requirements, we present an effective technical setup that can consistently repeat the same conditions between users and that can be easily replicated to other labs conducting cloud-based social XR research.

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Publication Details

Published
2025-01-10
DOI
https://doi.org/10.1109/ccnc54725.2025.10976077
Primary Topic
Image and Video Quality Assessment
Type
article
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article

A Demonstration of QoE Assessment for Cloud-based Social XR Applications over Mobile Networks

Karan Mitra, Christer Åhlund, Henrique Souza Rossi, Justin Gavrell
Image and Video Quality Assessment
article

A Demonstration of QoE Assessment for Cloud-based Social XR Applications over Mobile Networks

Karan Mitra, Christer Åhlund, Henrique Souza Rossi, Justin Gavrell
article en

Abstract

Cloud-based social eXtended Reality (XR) services are the cornerstone for realizing the promises of the Metaverse. These services hosted either on datacenters or edge, will demand stringent mobile network quality of service (QoS) to operate effectively and provide an acceptable user quality. It becomes fundamental to study how mobile networks QoS factors round-trip time (RTT), packet loss (PL), and jitter affect these services by measuring their effect on users' perceived quality of experience (QoE). Subjective QoE assessment involves carefully controlled laboratory environments to generate the desired conditions between a large set of users. The requirements for a cloud-based social XR service lab-setup are complex: Identify a reliable streaming service, a customizable VR application, emulate network conditions, define activities or tasks for users to perform, collect their data, label it; all while mitigating possible human mistakes. To address these requirements, we present an effective technical setup that can consistently repeat the same conditions between users and that can be easily replicated to other labs conducting cloud-based social XR research.

Luleå University of Technology (SE)
Openalex Percentile: Top 92%
Image and Video Quality Assessment
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A Demonstration of QoE Assessment for Cloud-based Social XR Applications over Mobile Networks — Karan Mitra, Christer Åhlund, et al. · (2025) | TGRS Research Map | TGRS