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Efficient resource allocation and scheduling mechanism of XR traffic

Published: 02 March 2023 Publication History

Abstract

EXtended reality (XR) has become one of the most important 5G and 5G-Advance media applications in the industry. Specifically, XR is a broad term covering augmented reality, mixed reality and virtual reality. Although XR traffic has some similar characteristics with URLLC traffic, there are also some differences, such as multiple periodic data streams, variable packets sizes and so on. Therefore, based on the analysis of XR-specific traffic, the paper aims to investigate efficient resource allocation and scheduling mechanism of XR traffic. For instance, with the configured grant (CG) transmission, the latency of uplink (UL) XR data flows can be reduced. In order to improve the reliability, K-repeated CG configuration can be considered. To help the gNB make efficient scheduling, the UE can also use the assistance information to indicate XR traffics’ quality requirements and time-aligned transmission to gNB. After that, the paper analyses and evaluates the efficiency of the UL grants allocation method. It shows that with the assistance information, the gNB can make priority classification and efficient resource allocation, which can reduce resources by up to 81%.

References

[1]
Alriksson, Fredrik, "XR and 5G: Extended reality at scale with time-critical communication." Ericsson Technology Review 2021.8 (2021): 2-13.
[2]
3GPP RP-201145: "Revised SI on XR Evaluations for XR" [S]. 2020.
[3]
3GPP RP-212711: “New SID on XR Enhancements for NR” [S]. 2021.
[4]
Bojkovic, Zoran, "6G ultra-low latency communication in future mobile XR applications." International Symposium on Signal Processing and Intelligent Recognition Systems. Springer, Singapore, 2021.
[5]
3GPP R1-2008454: “Views on XR application, traffic models and evaluation methodology” [S]. 2020.
[6]
3GPP RP-212996: “Discussion on Rel-18 XR” [S]. 2021.
[7]
Le, Trung-Kien, Umer Salim, and Florian Kaltenberger. "An overview of physical layer design for Ultra-Reliable Low-Latency Communications in 3GPP Releases 15, 16, and 17." IEEE access 9 (2020): 433-444.
[8]
Le, Trung-Kien, Umer Salim, and Florian Kaltenberger. "Enhancing URLLC uplink Configured-grant transmissions." 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring). IEEE, 2021.
[9]
3GPP TR 38.838: “Study on XR (Extended Reality) Evaluations for NR” [S]. 2021
[10]
Sen Xu, Jincan Xin. “A review of 5G uRLLC enhancement technology” [J], mobile communication, 2019,43(9): 62-67.
[11]
3GPP R1-2110811: “Performance evaluation results for XR and Cloud Gaming” [S]. 2021

Cited By

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  • (2024)Online Multi-User Scheduling for XR Transmissions With Hard-Latency Constraint: Performance Analysis and Practical DesignIEEE Transactions on Communications10.1109/TCOMM.2024.337044172:7(4055-4071)Online publication date: Jul-2024

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        CCEAI '23: Proceedings of the 7th International Conference on Control Engineering and Artificial Intelligence
        January 2023
        187 pages
        ISBN:9781450397513
        DOI:10.1145/3580219
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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        Published: 02 March 2023

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        • National Key R&D Program of China

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        • (2024)Online Multi-User Scheduling for XR Transmissions With Hard-Latency Constraint: Performance Analysis and Practical DesignIEEE Transactions on Communications10.1109/TCOMM.2024.337044172:7(4055-4071)Online publication date: Jul-2024

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