The Metaverse, an emerging digital space, is expected to offer various services mirroring the real world. Wireless communications for mobile Metaverse users should be tailored to meet the following user characteristics: 1) emphasizing application-specific utility instead of simply the transmission rate, 2) concerned with energy efficiency due to the limited device battery and energy-intensiveness of some applications, and 3) caring about security as the applications may involve sensitive personal data. To this end, this paper incorporates application-specific utility, energy efficiency, and physical-layer security (PLS) into the studied optimization in a wireless network for the Metaverse. Specifically, after introducing utility-energy efficiency (UEE) to represent each Metaverse user's application-specific objective under PLS, we formulate an optimization to maximize the network's weighted sum-UEE by deciding users' transmission powers and communication bandwidths. The formulated problem belongs to the sum-of-ratios optimization, for which prior studies have demonstrated its difficulty. Nevertheless, our proposed algorithm 1) obtains the global optimum for the optimization problem, via a transform to parametric convex optimization problems, 2) applies to any utility function which is concave, increasing, and twice differentiable, and 3) achieves a linear time complexity in the number of users (the optimal complexity in the order sense). Simulations confirm the superiority of our algorithm over other approaches. We envision that our technique for solving the challenging sum-of-ratios optimization can be applied to other optimization problems in wireless networks and mobile computing.
翻译:元数据是一个新兴的数字空间,它预计将提供反映真实世界的各种服务。移动元数据用户的无线通信应适应以下用户特点:1)强调具体应用的效用,而不是简单的传输率;2)由于设备电池有限和一些应用的能源密集度而关注能源效率;3)关注安全,因为应用可能涉及敏感的个人数据。为此,本文件将具体应用的效用、能源效率和物理安全(PLS)纳入Metavers的无线网络中研究的优化。具体来说,在采用公用事业能效(UE)来代表每个Metavers用户网络在PLS下的具体应用目标之后,我们制定了一种优化,通过决定用户的传输能力和通信带宽度来最大限度地提高网络的加权总和能量;以及3)由于应用的软件可能涉及敏感的个人数据,所提出的问题属于“总和”的优化,因为先前的研究表明它存在困难。然而,我们拟议的算法1(1)通过将优化问题转化为对优化问题的全球最佳处理方式。2)适用于在最优化性成本方面采用的任何实用功能,即以最优的精度计算方法,即以最优的精度为最精确的精度、最精确的精度,即以最精确的精度确认的精度为精度。</s>