用数字孪生优化移动端增强现实标注渲染的通信服务,提升体验同时节省资源。
QoE-oriented Communication Service Provision for Annotation Rendering in Mobile Augmented Reality
- 构建针对MAR应用的数字孪生模型,学习标注渲染机制。
- 精准建模用户QoE与资源需求关系,提升预测精度。
- 相比传统切片方案,降低资源消耗,适合6G边缘计算场景。
随着移动增强现实(MAR)的发展,未来6G网络将在支持沉浸式、个性化用户体验中发挥关键作用。本文针对边缘辅助MAR中的标注渲染通信服务提供问题,旨在优化频谱资源利用的同时保障用户所需的体验质量(QoE)。为应对用户上行数据流量模式差异及标注渲染复杂性,提出一种基于数字孪生(DT)的方法。首先设计专用于MAR应用的数字孪生模型,学习关键标注渲染机制,使网络控制器可获取应用级信息;其次构建基于数字孪生的QoE建模方法,捕捉个体用户QoE与频谱资源需求间的独特关联;最后提出面向QoE的资源分配算法,在保证QoE前提下降低资源使用率。仿真结果表明,该方法在QoE建模的准确性和粒度方面优于基准方案。
原文摘要 · Abstract (English)
As mobile augmented reality (MAR) continues to evolve, future 6G networks will play a pivotal role in supporting immersive and personalized user experiences. In this paper, we address the communication service provision problem for annotation rendering in edge-assisted MAR, with the objective of optimizing spectrum resource utilization while ensuring the required quality of experience (QoE) for MAR users. To overcome the challenges of user-specific uplink data traffic patterns and the complex operational mechanisms of annotation rendering, we propose a digital twin (DT)-based approach. We first design a DT specifically tailored for MAR applications to learn key annotation rendering mechanisms, enabling the network controller to access MAR application-specific information. Then, we develop a DT based QoE modeling approach to capture the unique relationship between individual user QoE and spectrum resource demands. Finally, we propose a QoE-oriented resource allocation algorithm that decreases resource utilization compared to conventional net work slicing-based approaches. Simulation results demonstrate that our DT-based approach outperforms benchmark approaches in the accuracy and granularity of QoE modeling.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。