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.

本文基于虚拟现实技术和 Metaverse 的背景，针对多用户场景下，提出了一种基于 DRL 算法的用户中心多通道帧生成和传输的方法 UCHA，以提升用户体验。