Throughput Prediction Using Recurrent Neural Network Model

被引：0

作者：

Wei, Bo ^{[1
]}

Okano, Mayuko ^{[1
]}

Kanai, Kenji ^{[1
]}

Kawakami, Wataru ^{[1
]}

Katto, Jiro ^{[1
]}

机构：

[1] Waseda Univ, Dept Comp Sci & Commun Engn, Tokyo, Japan

来源：

2018 IEEE 7TH GLOBAL CONFERENCE ON CONSUMER ELECTRONICS (GCCE 2018) | 2018年

关键词：

throughput prediction; RNN; mobile network;

D O I：

暂无

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：

To ensure good quality of experience for user when transmitting video content, throughput prediction can contribute to the selection of proper bitrate. In this paper, we propose a throughput prediction method with recurrent neural network (RNN) model. Experiments are conducted to evaluate the methods, and the results indicate that proposed method can decrease the prediction error by a maximum of 29.39% compared with traditional methods.

引用

页码：107 / 108

页数：2

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