User-centric Heterogeneous-action Deep Reinforcement Learning for
Virtual Reality in the Metaverse over Wireless Networks
- URL: http://arxiv.org/abs/2302.01471v2
- Date: Mon, 22 May 2023 17:42:11 GMT
- Title: User-centric Heterogeneous-action Deep Reinforcement Learning for
Virtual Reality in the Metaverse over Wireless Networks
- Authors: Wenhan Yu, Terence Jie Chua, Jun Zhao
- Abstract summary: In this paper, we consider a system consisting of a Metaverse server and multiple VR users.
In our multi-user VR scenario for the Metaverse, users have different characteristics and demands for Frames Per Second (FPS)
Our proposed user-centric DRL algorithm is called User-centric Critic with Heterogenous Actors (UCHA)
- Score: 8.513938423514636
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The Metaverse is emerging as maturing technologies are empowering the
different facets. Virtual Reality (VR) technologies serve as the backbone of
the virtual universe within the Metaverse to offer a highly immersive user
experience. As mobility is emphasized in the Metaverse context, VR devices
reduce their weights at the sacrifice of local computation abilities. In this
paper, for a system consisting of a Metaverse server and multiple VR users, we
consider two cases of (i) the server generating frames and transmitting them to
users, and (ii) users generating frames locally and thus consuming device
energy. Moreover, in our multi-user VR scenario for the Metaverse, users have
different characteristics and demands for Frames Per Second (FPS). Then the
channel access arrangement (including the decisions on frame generation
location), and transmission powers for the downlink communications from the
server to the users are jointly optimized to improve the utilities of users.
This joint optimization is addressed by deep reinforcement learning (DRL) with
heterogeneous actions. Our proposed user-centric DRL algorithm is called
User-centric Critic with Heterogenous Actors (UCHA). Extensive experiments
demonstrate that our UCHA algorithm leads to remarkable results under various
requirements and constraints.
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