Using Pixel-per-bit Neural Network for Two Rolling Shutter Patterns Decoding in Optical Camera Communication (OCC)

Deng Cheng Tsai; Yun Shen Lin; Yun Han Chang; Li Sheng Hsu; Chi Wai Chow; Yang Liu; Chien Hung Yeh; Kun Hsien Lin

doi:10.1109/WOCC53213.2021.9602893

Using Pixel-per-bit Neural Network for Two Rolling Shutter Patterns Decoding in Optical Camera Communication (OCC)

Deng Cheng Tsai, Yun Shen Lin, Yun Han Chang, Li Sheng Hsu, Chi Wai Chow, Yang Liu, Chien Hung Yeh, Kun Hsien Lin

Department of Photonics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Optical wireless communication (OWC) has received increasing attention recently. One application of OWC uses image sensor as optical receiver, which is known as optical camera communication (OCC). Rolling shutter mode in OCC allows data rate higher than the camera frame-rate operation. However, the row by row exposure delay will create decoding challenge, and high inter-symbol interference (ISI) can be observed in the rolling shutter pattern. In this work, we propose and demonstrate an OCC system employing pixel-per-bit (PPB) as label for the deep neural network (PPB-NN). Besides, two rolling shutter patterns emitted by two LED light panels can be decoded simultaneously. The proposed PPB-NN is also compared with other decoding schemes in the literature, and the experimental results revealed that the proposed scheme can achieve a better bit-error ratio (BER) performance.

Original language	English
Title of host publication	2021 30th Wireless and Optical Communications Conference, WOCC 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	102-105
Number of pages	4
ISBN (Electronic)	9781665427722
DOIs	https://doi.org/10.1109/WOCC53213.2021.9602893
State	Published - 2021
Event	30th Wireless and Optical Communications Conference, WOCC 2021 - Taipei, Taiwan Duration: 7 Oct 2021 → 8 Oct 2021

Publication series

Name	2021 30th Wireless and Optical Communications Conference, WOCC 2021

Conference

Conference	30th Wireless and Optical Communications Conference, WOCC 2021
Country/Territory	Taiwan
City	Taipei
Period	7/10/21 → 8/10/21

Keywords

Optical wireless communication (OWC)
light emitting diode (LED)
machine learning (ML)
optical camera communication (OCC)
rolling shutter

Access to Document

10.1109/WOCC53213.2021.9602893

Cite this

Tsai, D. C., Lin, Y. S., Chang, Y. H., Hsu, L. S., Chow, C. W., Liu, Y., Yeh, C. H., & Lin, K. H. (2021). Using Pixel-per-bit Neural Network for Two Rolling Shutter Patterns Decoding in Optical Camera Communication (OCC). In 2021 30th Wireless and Optical Communications Conference, WOCC 2021 (pp. 102-105). (2021 30th Wireless and Optical Communications Conference, WOCC 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WOCC53213.2021.9602893

Tsai, Deng Cheng ; Lin, Yun Shen ; Chang, Yun Han et al. / Using Pixel-per-bit Neural Network for Two Rolling Shutter Patterns Decoding in Optical Camera Communication (OCC). 2021 30th Wireless and Optical Communications Conference, WOCC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 102-105 (2021 30th Wireless and Optical Communications Conference, WOCC 2021).

@inproceedings{b711a9790e9b4958b58c627525114071,

title = "Using Pixel-per-bit Neural Network for Two Rolling Shutter Patterns Decoding in Optical Camera Communication (OCC)",

abstract = "Optical wireless communication (OWC) has received increasing attention recently. One application of OWC uses image sensor as optical receiver, which is known as optical camera communication (OCC). Rolling shutter mode in OCC allows data rate higher than the camera frame-rate operation. However, the row by row exposure delay will create decoding challenge, and high inter-symbol interference (ISI) can be observed in the rolling shutter pattern. In this work, we propose and demonstrate an OCC system employing pixel-per-bit (PPB) as label for the deep neural network (PPB-NN). Besides, two rolling shutter patterns emitted by two LED light panels can be decoded simultaneously. The proposed PPB-NN is also compared with other decoding schemes in the literature, and the experimental results revealed that the proposed scheme can achieve a better bit-error ratio (BER) performance.",

keywords = "Optical wireless communication (OWC), light emitting diode (LED), machine learning (ML), optical camera communication (OCC), rolling shutter",

author = "Tsai, {Deng Cheng} and Lin, {Yun Shen} and Chang, {Yun Han} and Hsu, {Li Sheng} and Chow, {Chi Wai} and Yang Liu and Yeh, {Chien Hung} and Lin, {Kun Hsien}",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 30th Wireless and Optical Communications Conference, WOCC 2021 ; Conference date: 07-10-2021 Through 08-10-2021",

year = "2021",

doi = "10.1109/WOCC53213.2021.9602893",

language = "English",

series = "2021 30th Wireless and Optical Communications Conference, WOCC 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "102--105",

booktitle = "2021 30th Wireless and Optical Communications Conference, WOCC 2021",

address = "美國",

}

Tsai, DC, Lin, YS, Chang, YH, Hsu, LS, Chow, CW, Liu, Y, Yeh, CH & Lin, KH 2021, Using Pixel-per-bit Neural Network for Two Rolling Shutter Patterns Decoding in Optical Camera Communication (OCC). in 2021 30th Wireless and Optical Communications Conference, WOCC 2021. 2021 30th Wireless and Optical Communications Conference, WOCC 2021, Institute of Electrical and Electronics Engineers Inc., pp. 102-105, 30th Wireless and Optical Communications Conference, WOCC 2021, Taipei, Taiwan, 7/10/21. https://doi.org/10.1109/WOCC53213.2021.9602893

Using Pixel-per-bit Neural Network for Two Rolling Shutter Patterns Decoding in Optical Camera Communication (OCC). / Tsai, Deng Cheng; Lin, Yun Shen; Chang, Yun Han et al.
2021 30th Wireless and Optical Communications Conference, WOCC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 102-105 (2021 30th Wireless and Optical Communications Conference, WOCC 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Using Pixel-per-bit Neural Network for Two Rolling Shutter Patterns Decoding in Optical Camera Communication (OCC)

AU - Tsai, Deng Cheng

AU - Lin, Yun Shen

AU - Chang, Yun Han

AU - Hsu, Li Sheng

AU - Chow, Chi Wai

AU - Liu, Yang

AU - Yeh, Chien Hung

AU - Lin, Kun Hsien

PY - 2021

Y1 - 2021

N2 - Optical wireless communication (OWC) has received increasing attention recently. One application of OWC uses image sensor as optical receiver, which is known as optical camera communication (OCC). Rolling shutter mode in OCC allows data rate higher than the camera frame-rate operation. However, the row by row exposure delay will create decoding challenge, and high inter-symbol interference (ISI) can be observed in the rolling shutter pattern. In this work, we propose and demonstrate an OCC system employing pixel-per-bit (PPB) as label for the deep neural network (PPB-NN). Besides, two rolling shutter patterns emitted by two LED light panels can be decoded simultaneously. The proposed PPB-NN is also compared with other decoding schemes in the literature, and the experimental results revealed that the proposed scheme can achieve a better bit-error ratio (BER) performance.

AB - Optical wireless communication (OWC) has received increasing attention recently. One application of OWC uses image sensor as optical receiver, which is known as optical camera communication (OCC). Rolling shutter mode in OCC allows data rate higher than the camera frame-rate operation. However, the row by row exposure delay will create decoding challenge, and high inter-symbol interference (ISI) can be observed in the rolling shutter pattern. In this work, we propose and demonstrate an OCC system employing pixel-per-bit (PPB) as label for the deep neural network (PPB-NN). Besides, two rolling shutter patterns emitted by two LED light panels can be decoded simultaneously. The proposed PPB-NN is also compared with other decoding schemes in the literature, and the experimental results revealed that the proposed scheme can achieve a better bit-error ratio (BER) performance.

KW - Optical wireless communication (OWC)

KW - light emitting diode (LED)

KW - machine learning (ML)

KW - optical camera communication (OCC)

KW - rolling shutter

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U2 - 10.1109/WOCC53213.2021.9602893

DO - 10.1109/WOCC53213.2021.9602893

M3 - Conference contribution

AN - SCOPUS:85123425883

T3 - 2021 30th Wireless and Optical Communications Conference, WOCC 2021

SP - 102

EP - 105

BT - 2021 30th Wireless and Optical Communications Conference, WOCC 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 30th Wireless and Optical Communications Conference, WOCC 2021

Y2 - 7 October 2021 through 8 October 2021

ER -

Tsai DC, Lin YS, Chang YH, Hsu LS, Chow CW, Liu Y et al. Using Pixel-per-bit Neural Network for Two Rolling Shutter Patterns Decoding in Optical Camera Communication (OCC). In 2021 30th Wireless and Optical Communications Conference, WOCC 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 102-105. (2021 30th Wireless and Optical Communications Conference, WOCC 2021). doi: 10.1109/WOCC53213.2021.9602893

Using Pixel-per-bit Neural Network for Two Rolling Shutter Patterns Decoding in Optical Camera Communication (OCC)

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Keywords

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