Study on fading prediction for automated guided vehicle using probabilistic neural network

Julian Webber, Norisato Suga, Abolfazl Mehbodniya, Kazuto Yano, Tomoaki Kumagai

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

This paper describes a technique to predict the fading channel of an automated guided vehicle (AGV) that moves along a pre-determined route. A probabilistic neural network (PNN) estimates the most likely signal by performing pattern matching between a stored and current fading signal window. The prediction unit is being developed as part of an anomaly detection unit that together will provide advance information on pending communication outages in a factory communications network. Multiple distributed receivers are employed in order to further improve the accuracy of the prediction. Performance is evaluated using a ray-tracing model of the moving AGV and results show that the mean squared error (MSE) can be reduced four orders of magnitude by employing eight receivers.

本文言語English
ホスト出版物のタイトル2018 Asia-Pacific Microwave Conference, APMC 2018 - Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ページ887-889
ページ数3
ISBN(電子版)9784902339451
DOI
出版ステータスPublished - 2019 1月 16
外部発表はい
イベント30th Asia-Pacific Microwave Conference, APMC 2018 - Kyoto, Japan
継続期間: 2018 11月 62018 11月 9

出版物シリーズ

名前Asia-Pacific Microwave Conference Proceedings, APMC
2018-November

Conference

Conference30th Asia-Pacific Microwave Conference, APMC 2018
国/地域Japan
CityKyoto
Period18/11/618/11/9

ASJC Scopus subject areas

  • 電子工学および電気工学

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