QoE-oriented Communication Service Provision for Annotation Rendering in Mobile Augmented Reality

TL;DR

This paper proposes a digital twin-based framework for optimizing spectrum resource allocation in edge-assisted mobile augmented reality, ensuring high quality of experience for users while reducing resource consumption.

Contribution

It introduces a novel digital twin approach for MAR that models annotation rendering and user QoE, enabling more efficient resource allocation.

Findings

DT-based QoE modeling improves accuracy over benchmarks

Resource allocation reduces spectrum usage compared to traditional methods

Enhanced QoE for MAR users with lower resource consumption

Abstract

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.