Presentation 2017-12-18
Propagation Loss Prediction By Machine Learning for Wireless LAN Cell Planning
Yunyi Yao, Kentaro Saito, Azril Haniz, Jun-ichi Takada,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Wireless Local Area Network (WLAN) is currently among the most important technologies for wireless broadband access. When it comes to WLAN cell planning, how to determine the position for access points in which they can provide better network performance is dependent on path loss prediction. This research proposes and evaluates a machine learning-based path loss model in order to provide more accurate path loss information for WLAN cell planning designers.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) PropagationPass lossWLANMachine Learning
Paper # SRW2017-62
Date of Issue 2017-12-11 (SRW)

Conference Information
Committee SRW
Conference Date 2017/12/18(1days)
Place (in Japanese) (See Japanese page)
Place (in English) Waseda Univ.
Topics (in Japanese) (See Japanese page)
Topics (in English) WLAN, WPAN, Sensor networ, mmWave, etc.
Chair Tadao Nakagawa(Tottori Univ.)
Vice Chair Satoshi Denno(Okayama Univ.) / Makoto Hamaminato(Fujitsu labs.)
Secretary Satoshi Denno(NICT) / Makoto Hamaminato(Kyoto Univ.)
Assistant Kentaro Saito(Tokyo Inst. of Tech.) / Hiromasa Yamauchi(Fujitsu labs.)

Paper Information
Registration To Technical Committee on Short Range Wireless Communications
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Propagation Loss Prediction By Machine Learning for Wireless LAN Cell Planning
Sub Title (in English)
Keyword(1) PropagationPass lossWLANMachine Learning
1st Author's Name Yunyi Yao
1st Author's Affiliation Tokyo Institute of Technology(Ti-tech)
2nd Author's Name Kentaro Saito
2nd Author's Affiliation Tokyo Institute of Technology(Ti-tech)
3rd Author's Name Azril Haniz
3rd Author's Affiliation Tokyo Institute of Technology(Ti-tech)
4th Author's Name Jun-ichi Takada
4th Author's Affiliation Tokyo Institute of Technology(Ti-tech)
Date 2017-12-18
Paper # SRW2017-62
Volume (vol) vol.117
Number (no) SRW-363
Page pp.pp.13-18(SRW),
#Pages 6
Date of Issue 2017-12-11 (SRW)