# Real-time Extended Reality Video Transmission Optimization Based on Frame-priority Scheduling

arXiv: https://arxiv.org/abs/2402.01180 · HTML: https://mlsanity.com/paper/2402.01180/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Feb 2024.

## Built on by (most cited first, 1 of 1)

- [The evolution of volumetric video: A survey of smart transcoding and compression approaches](https://mlsanity.com/paper/2411.02095/) (2024)

## Abstract (arXiv)

Extended reality (XR) is one of the most important applications of 5G. For real-time XR video transmission in 5G networks, a low latency and high data rate are required. In this paper, we propose a resource allocation scheme based on frame-priority scheduling to meet these requirements. The optimization problem is modelled as a frame-priority-based radio resource scheduling problem to improve transmission quality. We propose a scheduling framework based on multi-step Deep Q-network (MS-DQN) and design a neural network model based on convolutional neural network (CNN). Simulation results show that the scheduling framework based on frame-priority and MS-DQN can improve transmission quality by 49.9%-80.2%.