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Case for 5G-aware video streaming applications

Published: 23 August 2021 Publication History

Abstract

Recent measurement studies show that commercial mmWave 5G can indeed offer ultra-high bandwidth (up to 2 Gbps), capable of supporting bandwidth-intensive applications such as ultra-HD (UHD) 4K/8K and volumetric video streaming on mobile devices. However, mmWave 5G also exhibits highly variable throughput performance and incurs frequent handoffs (e.g., between 5G and 4G), due to its directional nature, signal blockage and other environmental factors, especially when the device is mobile. All these issues make it difficult for applications to achieve high Quality of Experience (QoE). In this paper, we advance several new mechanisms to tackle the challenges facing UHD video streaming applications over 5G networks, thereby making them {\em 5G-aware}. We argue for the need to employ machine learning (ML) for effective throughput prediction to aid applications in intelligent bitrate adaptation. Furthermore, we advocate {\em adaptive content bursting}, and {\em dynamic radio (band) switching} to allow the 5G radio network to fully utilize the available radio resources under good channel/beam conditions, whereas dynamically switched radio channels/bands (e.g., from 5G high-band to low-band, or 5G to 4G) to maintain session connectivity and ensure a minimal bitrate. We conduct initial evaluation using real-world 5G throughput measurement traces. Our results show these mechanisms can help minimize, if not completely eliminate, video stalls, despite wildly varying 5G throughput.

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cover image ACM Conferences
5G-MeMU '21: Proceedings of the 1st Workshop on 5G Measurements, Modeling, and Use Cases
August 2021
40 pages
ISBN:9781450386364
DOI:10.1145/3472771
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 ACM 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: 23 August 2021

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Author Tags

  1. 5G
  2. 5G throughput
  3. 5G-aware applications
  4. adaptive content bursting
  5. dynamic radio (band) switching
  6. mmWave
  7. volumetric video streaming

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SIGCOMM '21
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SIGCOMM '21: ACM SIGCOMM 2021 Conference
August 23, 2021
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  • (2024)Unveiling the Power of Arduino Zero for Next-Generation Aerial Communication with 5G and Drones2024 36th Conference of Open Innovations Association (FRUCT)10.23919/FRUCT64283.2024.10749848(381-389)Online publication date: 30-Oct-2024
  • (2024)Designing Network Algorithms via Large Language ModelsProceedings of the 23rd ACM Workshop on Hot Topics in Networks10.1145/3696348.3696868(205-212)Online publication date: 18-Nov-2024
  • (2024)YouTube goes 5G: QoE Benchmarking and ML-based Stall Prediction2024 IEEE Wireless Communications and Networking Conference (WCNC)10.1109/WCNC57260.2024.10571175(01-06)Online publication date: 21-Apr-2024
  • (2024)A Kalman Filter Based Low Complexity Throughput Prediction Algorithm for 5G Cellular NetworksIEEE Transactions on Vehicular Technology10.1109/TVT.2023.333964973:5(7089-7101)Online publication date: May-2024
  • (2024)MMVS: Enabling Robust Adaptive Video Streaming for Wildly Fluctuating and Heterogeneous NetworksIEEE Transactions on Multimedia10.1109/TMM.2024.344360926(11018-11030)Online publication date: 2024
  • (2024)The Chronicles of 5G Non-Standalone: An Empirical Analysis of Performance and Service EvolutionIEEE Open Journal of the Communications Society10.1109/OJCOMS.2024.34993705(7380-7399)Online publication date: 2024
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  • (2024)An Experimental Study of Low-Latency Video Streaming over 5G2024 IEEE International Mediterranean Conference on Communications and Networking (MeditCom)10.1109/MeditCom61057.2024.10621182(383-388)Online publication date: 8-Jul-2024
  • (2024)Neural Adaptive Video Streaming via Imitation Learning and Reinforcement Learning2024 IEEE 10th International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications (MAPE)10.1109/MAPE62875.2024.10813772(1-4)Online publication date: 27-Nov-2024
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