@inproceedings{6adf9483fb7542589cf7bd8699c12073,
title = "Real-time Extended Reality Video Transmission Optimization Based on Frame-priority Scheduling",
abstract = "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%.",
keywords = "deep Q-network, resource allocation, wireless extended reality",
author = "Guangjin Pan and Shugong Xu and Shunqing Zhang and Xiaojing Chen and Yanzan Sun",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 International Conference on Future Communications and Networks, FCN 2023 ; Conference date: 17-12-2023 Through 20-12-2023",
year = "2023",
doi = "10.1109/FCN60432.2023.10543601",
language = "English",
series = "2023 International Conference on Future Communications and Networks, FCN 2023 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2023 International Conference on Future Communications and Networks, FCN 2023 - Proceedings",
}