Enhancing 5G QoS Management for XR Traffic Through XR Loopback Mechanism

被引:8
|
作者
Bojovic, Biljana [1 ]
Lagen, Sandra [1 ]
Koutlia, Katerina [1 ]
Zhang, Xiaodi [2 ]
Wang, Ping [2 ]
Yu, Liwen [2 ]
机构
[1] Ctr Tecnol Telecomunicac Catalunya CTTC CERCA, Barcelona 08860, Spain
[2] Real Labs, Menlo Pk, CA 94025 USA
关键词
5G NR; QoS management; XR enhancements; XR loopback mechanism; open source system-level simulations; 5G-Advanced; NETWORKS;
D O I
10.1109/JSAC.2023.3273701
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
5G networks are designed to support a variety of services with highly demanding Quality-of-Service (QoS) requirements. This opened the door for novel extended reality (XR) media applications to emerge with 5G. However, recent 5G field tests and system-level simulation studies show that further XR enhancements are required to support a massive adoption of XR services in 5G networks. Such enhancements are expected to come into play with 5G-Advanced. In this line, we propose and study an XR loopback mechanism that adapts the XR traffic to the instantaneous 5G network conditions by exploiting an XR application feedback. We propose various XR loopback algorithms, strategies, and parameters' configurations and study their impact on the 5G end-to-end performance. We conduct extensive simulation campaigns by building realistic end-to-end 5G network scenarios with 3GPP mixed XR traffic setups. Results show that the proposed XR loopback mechanism can boost XR performance in 5G networks by adapting to 5G network conditions, while keeping the XR QoS requirements under control. We provide various insights and practical directions on XR loopback design that allow us to take full advantage of the 5G network capabilities and progress toward 5G-Advanced network design.
引用
收藏
页码:1772 / 1786
页数:15
相关论文
共 50 条
  • [31] 5G+XR开启智慧教育新时代
    孙伟
    吕云
    奚春雁
    宋文婷
    计算机教育, 2019, (12) : 1 - 2
  • [32] A QoS driven adaptive mechanism for downlink and uplink decoupling in 5G
    Bouras, Christos
    Kalogeropoulos, Rafail
    INTERNET OF THINGS, 2020, 11
  • [33] Real-Time Super-Resolution: A New Mechanism for XR over 5G-Advanced
    Chen, Weichao
    Cao, Youlong
    Qin, Yi
    Chen, Erkai
    Zhou, Guohua
    Li, Weichao
    2023 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, WCNC, 2023,
  • [34] 5G时代XR技术在广播电视节目制作中的应用
    李尤佳
    裘晗
    电视技术, 2022, 46 (10) : 61 - 64
  • [35] XR5944 is a potent inhibitor of estrogen receptors through a novel mechanism
    Punchihewa, Chandanamali
    Carver, Megan
    De Alba, Adrian
    Sidell, Neil
    Yang, Danzhou
    CANCER RESEARCH, 2008, 68 (09)
  • [36] 基于微型投影仪的5G+XR
    张永亮
    中国新通信, 2021, 23 (03) : 62 - 65
  • [37] Scalable and QoS-Aware Resource Allocation to Heterogeneous Traffic Flows in 5G
    Boujelben, Yassine
    IEEE INTERNET OF THINGS JOURNAL, 2021, 8 (20) : 15568 - 15581
  • [38] Enhancing 5G network slicing for IoT traffic with a novel clustering framework
    Min, Ziran
    Gokhale, Swapna
    Shekhar, Shashank
    Mahmoudi, Charif
    Kang, Zhuangwei
    Barve, Yogesh
    Gokhale, Aniruddha
    PERVASIVE AND MOBILE COMPUTING, 2024, 104
  • [39] Improving the QoS in 5G HetNets Through Cooperative Q-Learning
    Iqbal, Muhammad Usman
    Ansari, Ejaz Ahmad
    Akhtar, Saleem
    Khan, Ali Nawaz
    IEEE ACCESS, 2022, 10 : 19654 - 19676
  • [40] Improving QoS of 5G Video Streaming Through Network Exposure Function
    Horita, Koki
    Fukumoto, Norihiro
    Nakao, Akihiro
    IEEE CONFERENCE ON GLOBAL COMMUNICATIONS, GLOBECOM, 2023, : 375 - 380