Using logistic regression classification for mitigating high noise-ratio advisement light-panel in rolling-shutter based visible light communications

被引：29

作者：

Chuang, Yu-Cheng ^{[1
]}

Chow, Chi-Wai ^{[1
]}

Liu, Yang ^{[2
]}

Yeh, Chien-Hung ^{[3
]}

Liao, Xin-Lan ^{[4
]}

Lin, Kun-Hsien ^{[4
]}

Chen, Yi-Yuan ^{[4
]}

机构：

[1] Natl Chiao Tung Univ, Coll Elect & Comp Engn, Dept Photon, Hsinchu 30010, Taiwan

[2] Philips Elect Ltd, Shatin, Hong Kong, Peoples R China

[3] Feng Chia Univ, Dept Photon, Taichung 40724, Taiwan

[4] Ind Technol Res Inst, Zhudong, Taiwan

来源：

OPTICS EXPRESS | 2019年 / 27卷 / 21期

关键词：

CMOS IMAGE SENSOR; TRANSMISSION; PERFORMANCE;

D O I：

10.1364/OE.27.029924

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

We propose and experimentally demonstrated a light-panel and image sensor based visible light communication (VLC) system using machine learning (ML) algorithm. The ML algorithm is compared with the traditional demodulation scheme and the experimental results show that even at very high noise-ratio (NR) light-panel display content, the proposed ML algorithm shows significant bit error rate (BER) improvement. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

引用

页码：29924 / 29929

页数：6

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