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Throughput Prediction on 60 GHz Mobile Devices for High-Bandwidth, Latency-Sensitive Applications

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Passive and Active Measurement (PAM 2021)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 12671))

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Abstract

In the near future, high quality VR and video streaming at 4K/8K resolutions will require Gigabit throughput to maintain a high user quality of experience (QoE). IEEE 802.11ad, which standardizes the 14 GHz of unlicensed spectrum around 60 GHz, is a prime candidate to fulfil these demands wirelessly. To maintain QoE, applications need to adapt to the ever changing network conditions by performing quality adaptation. A key component of quality adaptation is throughput prediction. At 60 GHz, due to the much higher frequency, the throughput can vary sharply due to blockage and mobility. Hence, the problem of predicting throughput becomes quite challenging.

In this paper, we perform an extensive measurement study of the predictability of the network throughput of an 802.11ad WLAN in downloading data to an 802.11ad-enabled mobile device under varying mobility patterns and orientations of the mobile device. We show that, with carefully designed neural networks, we can predict the throughput of the 60 GHz link with good accuracy at varying timescales, from 10 ms (suitable for VR) up to 2 s (suitable for ABR streaming). We further identify the most important features that affect the neural network prediction accuracy to be past throughput and MCS.

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Acknowledgements

We thank our shepherd, Prof. Özgü Alay, and the anonymous reviewers for their valuable comments. This work was supported in part by the NSF grant CNS-1553447.

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Authors and Affiliations

  1. Northeastern University, Boston, USA

    Shivang Aggarwal, Moinak Ghoshal & Dimitrios Koutsonikolas

  2. Purdue University, West Lafayette, USA

    Zhaoning Kong & Y. Charlie Hu

Authors
  1. Shivang Aggarwal
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  2. Zhaoning Kong
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  3. Moinak Ghoshal
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  4. Y. Charlie Hu
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  5. Dimitrios Koutsonikolas
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Corresponding author

Correspondence to Shivang Aggarwal .

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Editors and Affiliations

  1. Brandenburg University of Technology (BTU), Cottbus, Germany

    Oliver Hohlfeld

  2. Telefonica Research, Barcelona, Spain

    Andra Lutu

  3. Iribe Center, University of Maryland, College Park, MD, USA

    Dave Levin

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Aggarwal, S., Kong, Z., Ghoshal, M., Hu, Y.C., Koutsonikolas, D. (2021). Throughput Prediction on 60 GHz Mobile Devices for High-Bandwidth, Latency-Sensitive Applications. In: Hohlfeld, O., Lutu, A., Levin, D. (eds) Passive and Active Measurement. PAM 2021. Lecture Notes in Computer Science(), vol 12671. Springer, Cham. https://doi.org/10.1007/978-3-030-72582-2_30

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  • DOI: https://doi.org/10.1007/978-3-030-72582-2_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-72581-5

  • Online ISBN: 978-3-030-72582-2

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