mlsanityData to 14 Oct 2026

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

arXiv 2509.25905 ↗First posted 30 Sep 2025cs.NI cs.AIcited by 1

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Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 15 of its 54 references that are in the map. First posted on arXiv 30 Sep 2025.

Builds on

15 of 54 references.

References · 15

  1. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,361
  2. 2020ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAMcited by 878
  3. 2019N-BEATS: Neural basis expansion analysis for interpretable time series forecastingcited by 753
  4. 2014Long Short-Term Memory Based Recurrent Neural Network Architectures for Large Vocabulary Speech Recognitioncited by 111
  5. 2018InteriorNet: Mega-scale Multi-sensor Photo-realistic Indoor Scenes Datasetcited by 87
  6. 2023Toward Immersive Communications in 6Gcited by 17
  7. 2024Knowledge-Driven Deep Learning Paradigms for Wireless Network Optimization in 6Gcited by 15
  8. 2023Holistic Network Virtualization and Pervasive Network Intelligence for 6Gcited by 14
  9. 2022LEAF + AIO: Edge-Assisted Energy-Aware Object Detection for Mobile Augmented Realitycited by 9
  10. 2016Attention and Anticipation in Fast Visual-Inertial Navigationcited by 8
  11. 2023Digital Twin-based 3D Map Management for Edge-assisted Device Pose Tracking in Mobile ARcited by 7
  12. 2023AdaptSLAM: Edge-Assisted Adaptive SLAM with Resource Constraints via Uncertainty Minimizationcited by 6
3 more
  1. 2024User-centric Immersive Communications in 6G: A Data-oriented Framework via Digital Twincited by 5
  2. 2024Adaptive Device-Edge Collaboration on DNN Inference in AIoT: A Digital Twin-Assisted Approachcited by 4
  3. 2024User-centric Service Provision for Edge-assisted Mobile AR: A Digital Twin-based Approachcited by 1

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