Immersive volumetric video streaming in extended reality (XR) demands ultra-low motion-to-photon (MTP) latency, which conventional edge-centric architectures struggle to meet due to per-frame computationally intensive rendering tightly coupled with user motion. To address this challenge, we propose an Open Radio Access Network (O-RAN)-integrated playback framework that jointly orchestrates radio, compute, and content resources in near real time (Near-RT) control loop. The system formulates the rendered-pixel ratio as a continuous control variable and jointly optimizes it over the Open Cloud (O-Cloud) compute, gNB transmit power, and bandwidth under a Weber-Fechner quality of experience (QoE) model, explicitly balancing resolution, computation, and latency. A Soft Actor-Critic (SAC) agent with structured action decomposition and QoE-aware reward shaping resolves the resulting high-dimensional control problem. Experiments on a 5G O-RAN testbed and system simulations show that SAC reduces median MTP latency by above 11% and improves both mean QoE and fairness, demonstrating the feasibility of RIC-driven joint radio-compute-content control for scalable, latency-aware immersive streaming.
@article{arxiv.2601.20625,
title = {Immersive Volumetric Video Playback: Near-RT Resource Allocation and O-RAN-based Implementation},
author = {Yao Wen and Luping Xiang and Kun Yang},
journal= {arXiv preprint arXiv:2601.20625},
year = {2026}
}
Comments
Accepted to TMC, IEEE Transactions on Mobile Computing. https://doi.org/10.1109/TMC.2026.3674975