Virtual reality in metaverse over wireless networks with user-centered deep reinforcement learning

The Metaverse and its promises are fast becoming reality as maturing technologies are empowering the different facets. One of the highlights of the Metaverse is that it offers the possibility for highly immersive and interactive socialization. Virtual reality (VR) technologies are the backbone for t...

Full description

Saved in:
Bibliographic Details
Main Authors: Yu, Wenhan, Chua, Terence Jie, Zhao, Jun
Other Authors: Interdisciplinary Graduate School (IGS)
Format: Conference or Workshop Item
Language:English
Published: 2023
Subjects:
Online Access:https://hdl.handle.net/10356/170134
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-170134
record_format dspace
spelling sg-ntu-dr.10356-1701342023-10-29T15:36:01Z Virtual reality in metaverse over wireless networks with user-centered deep reinforcement learning Yu, Wenhan Chua, Terence Jie Zhao, Jun Interdisciplinary Graduate School (IGS) School of Computer Science and Engineering IEEE International Conference on Communications (ICC 2023) Engineering::Computer science and engineering Metaverse Computation Offloading Reinforcement Learning Wireless Networks The Metaverse and its promises are fast becoming reality as maturing technologies are empowering the different facets. One of the highlights of the Metaverse is that it offers the possibility for highly immersive and interactive socialization. Virtual reality (VR) technologies are the backbone for the virtual universe within the Metaverse as they enable a hyper-realistic and immersive experience, and especially so in the context of socialization. As the virtual world 3D scenes to be rendered are of high resolution and frame rate, these scenes will be offloaded to an edge server for computation. Besides, the metaverse is user-center by design, and human users are always the core. In this work, we introduce a multi-user VR computation offloading over wireless communication scenario. In addition, we devised a novel user-centered deep reinforcement learning approach to find a near-optimal solution. Extensive experiments demonstrate that our approach can lead to remarkable results under various requirements and constraints. Ministry of Education (MOE) Submitted/Accepted version This research is partly supported by the Singapore Ministry of Education Academic Research Fund under Grant Tier 1 RG90/22, RG97/20, Grant Tier 1 RG24/20 and Grant Tier 2 MOE2019-T2-1-176; and partly by the NTU-Wallenberg AI, Autonomous Systems and Software Program (WASP) Joint Project. 2023-10-24T01:06:37Z 2023-10-24T01:06:37Z 2023 Conference Paper Yu, W., Chua, T. J. & Zhao, J. (2023). Virtual reality in metaverse over wireless networks with user-centered deep reinforcement learning. IEEE International Conference on Communications (ICC 2023). https://dx.doi.org/10.1109/ICC45041.2023.10278715 978-1-5386-7462-8 1938-1883 https://hdl.handle.net/10356/170134 10.1109/ICC45041.2023.10278715 en RG90/22 RG97/20 RG24/20 MOE2019-T2-1-176 © 2023 IEEE. All rights reserved. This article may be downloaded for personal use only. Any other use requires prior permission of the copyright holder. The Version of Record is available online at http://doi.org/10.1109/ICC45041.2023.10278715. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering
Metaverse
Computation Offloading
Reinforcement Learning
Wireless Networks
spellingShingle Engineering::Computer science and engineering
Metaverse
Computation Offloading
Reinforcement Learning
Wireless Networks
Yu, Wenhan
Chua, Terence Jie
Zhao, Jun
Virtual reality in metaverse over wireless networks with user-centered deep reinforcement learning
description The Metaverse and its promises are fast becoming reality as maturing technologies are empowering the different facets. One of the highlights of the Metaverse is that it offers the possibility for highly immersive and interactive socialization. Virtual reality (VR) technologies are the backbone for the virtual universe within the Metaverse as they enable a hyper-realistic and immersive experience, and especially so in the context of socialization. As the virtual world 3D scenes to be rendered are of high resolution and frame rate, these scenes will be offloaded to an edge server for computation. Besides, the metaverse is user-center by design, and human users are always the core. In this work, we introduce a multi-user VR computation offloading over wireless communication scenario. In addition, we devised a novel user-centered deep reinforcement learning approach to find a near-optimal solution. Extensive experiments demonstrate that our approach can lead to remarkable results under various requirements and constraints.
author2 Interdisciplinary Graduate School (IGS)
author_facet Interdisciplinary Graduate School (IGS)
Yu, Wenhan
Chua, Terence Jie
Zhao, Jun
format Conference or Workshop Item
author Yu, Wenhan
Chua, Terence Jie
Zhao, Jun
author_sort Yu, Wenhan
title Virtual reality in metaverse over wireless networks with user-centered deep reinforcement learning
title_short Virtual reality in metaverse over wireless networks with user-centered deep reinforcement learning
title_full Virtual reality in metaverse over wireless networks with user-centered deep reinforcement learning
title_fullStr Virtual reality in metaverse over wireless networks with user-centered deep reinforcement learning
title_full_unstemmed Virtual reality in metaverse over wireless networks with user-centered deep reinforcement learning
title_sort virtual reality in metaverse over wireless networks with user-centered deep reinforcement learning
publishDate 2023
url https://hdl.handle.net/10356/170134
_version_ 1781793800864137216