2025/03/08 by Yuxuan Li, Li, Yuxuan, Sheng Jinag +3
Computer Science · Engineering · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Image and Video Quality Assessment #IoT and Edge/Fog Computing #Multimedia (cs.MM) #Telecommunications and Broadcasting Technologies
paper · pdf · doi:10.48550/arxiv.2506.10001
openalex publication_date 2025/03/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
With technology advancing and the pursuit of new audiovisual experiences strengthening, the metaverse has gained surging enthusiasm. However, it faces practical hurdles as substantial data like high-resolution virtual scenes must be transmitted between cloud platforms and VR devices. Specifically, the VR device's wireless transmission hampered by insufficient bandwidth, causes speed and delay problems. Meanwhile, poor channel quality leads to data errors and worsens user experience. To solve this, we've proposed the Semantic Communication-Enabled Cloud-Edge-End Collaborative Immersive Metaverse Service (SC-CEE-Meta) Architecture, which includes three modules: VR video semantic transmission, video synthesis, and 3D virtual scene reconstruction. By deploying semantic modules on VR devices and edge servers and sending key semantic info instead of focusing on bit-level reconstruction, it can cut latency, resolve the resource-bandwidth conflict, and better withstand channel interference. Also, the cloud deploys video synthesis and 3D scene reconstruction preprocessing, while edge devices host 3D reconstruction rendering modules, all for immersive services. Verified on Meta Quest Pro, the SC-CEE-Meta can reduce wireless transmission delay by 96.05% and boost image quality by 43.99% under poor channel condition.