Chyad, A., Shah, S.D.A., Qazzaz, M.M.H. et al. (2 more authors) (2025) Modelling 6Dof Vr Gaming Traffic for Next-Generation Networks. In: 2025 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit). European Conference on Networks and Communications (EuCNC), 03-06 Jun 2025, Poznan, Poland. . Institute of Electrical and Electronics Engineers (IEEE), pp. 157-162. ISBN: 979-8-3503-9181-7. ISSN: 2475-6490. EISSN: 2575-4912.
Abstract
The increasing adoption of Extended Reality (XR) applications demands advanced traffic modelling to optimise next-generation wireless networks. Existing models often rely on fixed data rates (e.g., 50 Mbps) and frame rates (e.g., 60Hz), which are insufficient for modern VR systems. This paper introduces an enhanced traffic modelling framework for highly interactive 6-degree-of-freedom (6DoF) VR gaming, incorporating video, audio, and control streams with support for higher frame rates (up to 120 Hz) and data rates (up to 251.9 Mbps). Built on empirical data from a high-fidelity VR setup, the model uses statistical analysis to fit data rate and inter-arrival times to probability distributions. The generalized logistic distribution is identified as the best fit for data rates, while the generalized extreme value distribution accurately represents inter-arrival times. Model accuracy is validated using Kullback-Leibler divergence. The findings offer critical insights for traffic generation, network planning, and resource allocation, supporting scalable and immersive XR experiences in future wireless networks.
Metadata
| Item Type: | Proceedings Paper |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | This is an author produced version of a conference paper published in 2025 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit) made available via the University of Leeds Research Outputs Policy under the terms of the Creative Commons Attribution License (CC-BY), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
| Keywords: | Experimental VR traffic generation; VR traffic modelling; Edge computing |
| Dates: |
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| Institution: | The University of Leeds |
| Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) |
| Date Deposited: | 24 Jun 2026 10:19 |
| Last Modified: | 24 Jun 2026 10:19 |
| Status: | Published |
| Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
| Identification Number: | 10.1109/eucnc/6gsummit63408.2025.11037170 |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:241972 |
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Filename: Modelling_6Dof_Vr_Gaming_Traffic_for_Next-Generation_Networks.pdf
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