Performance evaluation of object detection utilizing channel state information in wireless LAN systems with distributed antennas

Keisuke Takata, Osamu Muta, Tomoki Murakami, Shinya Otsuki

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

1 被引用数 (Scopus)

抄録

In this paper, we investigate a machine learning based object detection scheme utilizing channel state information (CSI) in wireless local area network (WLAN) systems with multiple distributed antennas, and evaluate the impact of antenna placement on achieved detection probability, where CSI frames captured from nearby wireless devices are used for machine learning based object detection. To improve the objective detection accuracy, we also investigate a method to distribute transmit and receive antennas in a target area for acquiring sufficient amount of CSI, where support vector machine (SVM) is used as a supervised machine learning algorithm. For performance evaluation, we used compressed CSI specified in IEEE 802.11ac standard and conduct a ray-tracing simulation in an indoor propagation environment for analyzing data and detecting a target object. Simulation results show that object detection probability can be improved by properly distributing antenna elements in a target area.

本文言語英語
ホスト出版物のタイトルWPMC 2020 - 23rd International Symposium on Wireless Personal Multimedia Communications
ホスト出版物のサブタイトルBridging Wireless and Business Worlds
出版社IEEE Computer Society
ISBN(電子版)9781728182964
DOI
出版ステータス出版済み - 10月 19 2020
イベント23rd International Symposium on Wireless Personal Multimedia Communications, WPMC 2020 - Virtual, Okayama, 日本
継続期間: 10月 19 202010月 26 2020

出版物シリーズ

名前International Symposium on Wireless Personal Multimedia Communications, WPMC
2020-October
ISSN(印刷版)1347-6890

会議

会議23rd International Symposium on Wireless Personal Multimedia Communications, WPMC 2020
国/地域日本
CityVirtual, Okayama
Period10/19/2010/26/20

!!!All Science Journal Classification (ASJC) codes

  • コンピュータ ネットワークおよび通信
  • コンピュータ サイエンスの応用
  • 人間とコンピュータの相互作用

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