Presentation 2018-07-11
Throughput Prediction Method based on machine learning in Mobile Networks
Bo Wei, kenji Kanai, Wataru Kawakami, Jiro Katto,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Throughput prediction is essential for providing high quality of service for video streaming transmissions. In this paper, we propose a TCP throughput prediction method using machine learning for mobile networks. In the TCP throughput prediction stage, the long short-term memory (LSTM) model is employed, which takes communication quality factors, sensor data and scenario information into consideration. Field experiments are conducted to evaluate the proposal in various scenarios. The results show that proposed method can predict throughput accurately and decrease the prediction error compared with traditional methods.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Throughput predictionCommunication qualityMachine learningMobile networks
Paper # NS2018-42
Date of Issue 2018-07-04 (NS)

Conference Information
Committee ASN / NS / RCS / SR / RCC
Conference Date 2018/7/11(3days)
Place (in Japanese) (See Japanese page)
Place (in English) Hakodate Arena
Topics (in Japanese) (See Japanese page)
Topics (in English) Wireless Distributed Network, Machine Learning and AI for Wireless Communications and Networks, M2M (Machine-to-Machine), D2D (Device-to-Device), IoT(Internet of Things), etc.
Chair Hiraku Okada(Nagoya Univ.) / Yoshikatsu Okazaki(NTT) / Tomoaki Otsuki(Keio Univ.) / Kenta Umebayashi(Tokyo Univ. of Agric. and Tech.) / Kazunori Hayashi(Osaka City Univ.)
Vice Chair Koji Yamamoto(Kyoto Univ.) / Jin Nakazawa(Keio Univ.) / Kazuya Monden(Hitachi) / Akihiro Nakao(Univ. of Tokyo) / Eisuke Fukuda(Fujitsu Labs.) / Satoshi Suyama(NTT DoCoMo) / Fumiaki Maehara(Waseda Univ.) / Masayuki Ariyoshi(NEC) / Suguru Kameda(Tohoku Univ.) / Shunichi Azuma(Nagoya Univ.) / HUAN-BANG LI(NICT)
Secretary Koji Yamamoto(NICT) / Jin Nakazawa(Sophia Univ.) / Kazuya Monden(Kanagawa Inst. of Tech.) / Akihiro Nakao(NTT) / Eisuke Fukuda(Osaka Pref Univ.) / Satoshi Suyama(Hokkaido Univ.) / Fumiaki Maehara(NTT) / Masayuki Ariyoshi(NICT) / Suguru Kameda(ATR) / Shunichi Azuma(Univ. of Electro-Comm.) / HUAN-BANG LI(Kagawa Univ.)
Assistant Masafumi Hashimoto(Osaka Univ.) / Tomoyuki Ota(Hiroshima City Univ.) / Tatsuya Kikuzuki(Fujitu Lab.) / Ryo Nakano(HITACHI) / Yoshifumi Hotta(Mitsubishi Electric) / Kenichi Kashibuchi(NTT) / Kazushi Muraoka(NTT DOCOMO) / Shinsuke Ibi(Osaka Univ.) / Hiroshi Nishimoto(Mitsubishi Electric) / Koichi Adachi(Univ. of Electro-Comm.) / Osamu Nakamura(Sharp) / Gia Khanh Tran(Tokyo Inst. of Tech.) / Syusuke Narieda(Mie Univ.) / Koji Ohshima(Kozo Keikaku Engineering) / Mai Ohta(Fukuoka Univ.) / Teppei Oyama(Fujitsu Lab.) / Toshinori Kagawa(NICT) / Masateru Ogura(NAIST)

Paper Information
Registration To Technical Committee on Ambient intelligence and Sensor Networks / Technical Committee on Network Systems / Technical Committee on Radio Communication Systems / Technical Committee on Smart Radio / Technical Committee on Reliable Communication and Control
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Throughput Prediction Method based on machine learning in Mobile Networks
Sub Title (in English)
Keyword(1) Throughput predictionCommunication qualityMachine learningMobile networks
1st Author's Name Bo Wei
1st Author's Affiliation Waseda University(Waseda Univ.)
2nd Author's Name kenji Kanai
2nd Author's Affiliation Waseda University(Waseda Univ.)
3rd Author's Name Wataru Kawakami
3rd Author's Affiliation Waseda University(Waseda Univ.)
4th Author's Name Jiro Katto
4th Author's Affiliation Waseda University(Waseda Univ.)
Date 2018-07-11
Paper # NS2018-42
Volume (vol) vol.118
Number (no) NS-124
Page pp.pp.31-36(NS),
#Pages 6
Date of Issue 2018-07-04 (NS)