Throughput Prediction on 60 GHz Mobile Devices for High-Bandwidth, Latency-Sensitive Applications
Throughput Prediction on 60 GHz Mobile Devices for High-Bandwidth, Latency-Sensitive Applications
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DOI：
10.1007/978-3-030-72582-2_30
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
Shivang Aggarwal;Z. Kong;Moinak Ghoshal;Y. C. Hu;Dimitrios Koutsonikolas
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文献类型：
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作者：
Shivang Aggarwal;Z. Kong;Moinak Ghoshal;Y. C. Hu;Dimitrios Koutsonikolas
在不久的将来，4K/8 K分辨率的高质量VR和视频流将需要千兆吞吐量来保持高用户体验质量（QoE）。IEEE 802.11ad将14 GHz的非授权频谱扩展到60 GHz左右，是无线满足这些需求的主要候选方案。为了保持QoE，应用需要通过执行质量适配来适应不断变化的网络条件。质量自适应的一个关键组成部分是吞吐量预测。在60 GHz时，由于频率高得多，由于阻塞和移动性，吞吐量可能会急剧变化。因此，预测吞吐量的问题变得相当challenging.In本文中，我们进行了广泛的测量研究的可预测性的网络吞吐量的802.11ad无线局域网在下载数据到802.11ad使能的移动终端在不同的移动模式和方向的移动终端。我们表明，精心设计的神经网络，我们可以预测的吞吐量的60 GHz的链路具有良好的精度在不同的时间尺度，从10毫秒（适合VR）到2秒（适合ABR流）。我们进一步确定了影响神经网络预测精度的最重要的特征是过去的吞吐量和MCS。
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.