User-Centric Communication Service Provision for Edge-Assisted Mobile Augmented Reality

2025-09-30

AI Summary

In 6G edge-assisted mobile augmented reality (MAR), highly personalized and non-stationary uplink traffic from users causes excessive SLAM camera frame upload latency. Method: This paper proposes a user-centric digital twin communication service framework. Its core innovation lies in (i) a lightweight digital twin data model tailored for MAR devices, and (ii) a dual-operation-function coordination mechanism enabling adaptive switching of data-driven models to support dynamic traffic modeling and individualized resource scheduling. The framework integrates SLAM pose tracking modeling, time-aware traffic prediction, and robust resource allocation, validated via trajectory-driven simulation. Contribution/Results: Compared with 5G network slicing, the proposed framework improves SLAM frame upload timeliness by 14.2% under stringent latency constraints, while significantly enhancing system robustness against modeling errors and ensuring consistent immersive user experience.

Technology Category

• Planning, Routing, and Scheduling: Planning with Language Models
• Multiagent Systems: Agent Communication
• Application Domains: Mobility, Driving & Flight

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web applications in cross-disciplinary domains and verticals such as mixed reality, smart cities, and digital health
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation

Abstract

Future 6G networks are envisioned to facilitate edge-assisted mobile augmented reality (MAR) via strengthening the collaboration between MAR devices and edge servers. In order to provide immersive user experiences, MAR devices must timely upload camera frames to an edge server for simultaneous localization and mapping (SLAM)-based device pose tracking. In this paper, to cope with user-specific and non-stationary uplink data traffic, we develop a digital twin (DT)-based approach for user-centric communication service provision for MAR. Specifically, to establish DTs for individual MAR devices, we first construct a data model customized for MAR that captures the intricate impact of the SLAM-based frame uploading mechanism on the user-specific data traffic pattern. We then define two DT operation functions that cooperatively enable adaptive switching between different data-driven models for capturing non-stationary data traffic. Leveraging the user-oriented data management introduced by DTs, we propose an algorithm for network resource management that ensures the timeliness of frame uploading and the robustness against inherent inaccuracies in data traffic modeling for individual MAR devices. Trace-driven simulation results demonstrate that the user-centric communication service provision achieves a 14.2% increase in meeting the camera frame uploading delay requirement in comparison with the slicing-based communication service provision widely used for 5G.

Problem

• Optimizing uplink data traffic for mobile augmented reality devices
• Developing digital twin approach for user-centric communication service
• Ensuring timely frame uploading and robust network resource management

Innovation

• Digital twin approach for user-centric MAR communication
• Customized data model capturing SLAM-based traffic patterns
• Adaptive switching algorithm for non-stationary data traffic