The Metaverse will provide numerous immersive applications for human users, by consolidating technologies like extended reality (XR), video streaming, and cellular networks. Optimizing wireless communications to enable the human-centric Metaverse is important to satisfy the demands of mobile users. In this paper, we formulate the optimization of the system utility-cost ratio (UCR) for the Metaverse over wireless networks. Our human-centric utility measure for virtual reality (VR) applications of the Metaverse represents users' perceptual assessment of the VR video quality as a function of the data rate and the video resolution, and is learnt from real datasets. The variables jointly optimized in our problem include the allocation of both communication and computation resources as well as VR video resolutions. The system cost in our problem comprises the energy consumption and delay, and is non-convex with respect to the optimization variables due to fractions in the mathematical expressions. To solve the non-convex optimization, we develop a novel fractional programming technique, which contributes to optimization theory and has broad applicability beyond our paper. Our proposed algorithm for the system UCR optimization is computationally efficient and finds a stationary point to the constrained optimization. Through extensive simulations, our algorithm is demonstrated to outperform other approaches.

翻译：元宇宙将通过整合扩展现实（XR）、视频流媒体和蜂窝网络等技术，为人类用户提供大量沉浸式应用。优化无线通信以实现面向人类的元宇宙，对于满足移动用户的需求至关重要。本文针对无线网络中的元宇宙，提出了系统效用成本比（UCR）的优化方案。我们为元宇宙中的虚拟现实（VR）应用设计了一种面向人类的效用衡量标准，该标准将用户对VR视频质量的感知评估表示为数据速率和视频分辨率的函数，并通过真实数据集进行学习。在我们的问题中，联合优化的变量包括通信和计算资源的分配以及VR视频分辨率。系统成本包含能耗与延迟，由于数学表达式中存在分数项，该成本相对于优化变量呈现非凸性。为解决这一非凸优化问题，我们提出了一种新的分数规划技术，该技术不仅有助于优化理论的发展，而且具有超出本文的广泛适用性。我们提出的系统UCR优化算法计算效率高，并且能够找到约束优化问题的驻点。通过大量仿真实验，该算法被证明优于其他方法。