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Toward 6G-based metaverse : supporting highly-dynamic deterministic multi-user extended reality services

Yu, Hao; Shokrnezhad, Masoud; Taleb, Tarik; Li, Richard; Song, JaeSeung (2023-10-24)

 
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https://doi.org/10.1109/MNET.004.2300101

Yu, Hao
Shokrnezhad, Masoud
Taleb, Tarik
Li, Richard
Song, JaeSeung
Institute of Electrical and Electronics Engineers
24.10.2023

H. Yu, M. Shokrnezhad, T. Taleb, R. Li and J. Song, "Toward 6G-Based Metaverse: Supporting Highly-Dynamic Deterministic Multi-User Extended Reality Services," in IEEE Network, vol. 37, no. 4, pp. 30-38, July/August 2023, doi: 10.1109/MNET.004.2300101

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doi:https://doi.org/10.1109/MNET.004.2300101
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Abstract

Metaverse is the concept of a fully immersive and universal virtual space for multiuser interaction, collaboration, and socializing; forming the next evolution of the Internet. Metaverse depends on the convergence of multiple broad technologies that enable eXtended Reality (XR), which is an umbrella term for technologies that lie on the reality-virtuality continuum, namely Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR). Compared to streaming volumetric content to a single user, the XR applications that involve multiple users who simultaneously watch the same volumetric content (e.g., VR-based online training/ education and multi-user online gaming) are much more attractive. Multi-user XR/Metaverse puts additional demand on the underlying networks, making it more difficult to offer high-quality immersive material in real-time. To cope with this, in this article, we present a comprehensive system and component design for immersive and seamless multi-user XR experiences. To satisfy the Quality of Experience/Quality of Service (QoE/ QoS) requirements and especially stream synchronization requirement in XR collaboration scenarios, we propose an AI-powered deterministic multi-user extended reality resource orchestrator (PRECISENESS) that aims to solve the multi-user XR service provisioning problem. Finally, we demonstrate the performance of our proposed solution in a single-site multi-user XR use case. The obtained results demonstrate that our solution can deliver high-quality immersive XR services.

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