Deep learning-aided binary visible light communication systems

Hoon Lee; Tony Q.S. Quek; Sang Hyun Lee

doi:10.1109/GCWkshps45667.2019.9024576

Deep learning-aided binary visible light communication systems

Hoon Lee, Tony Q.S. Quek, Sang Hyun Lee

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

1 Citation (Scopus)

Abstract

This paper investigates a deep learning (DL) method for on-off keying (OOK) based visible light communication (VLC) systems where a lighting emitting diode transmits binary optical pulses to a receiver. Universal dimming abilities are considered such that the VLC transceiver meets arbitrary dimming requirement of external users. This poses a combinatorial formulation optimizing binary codewords under multiple dimming constraints. To tackle this, DL techniques are employed to design an OOK encoder-decoder pair over noisy optical channels. For universal dimming support, the training of the DL-based VLC transceiver turns out to be a constrained training problem with multiple dimming constraints. This paper employs a dual formulation to develop a constrained training strategy. Numerical results show the effectiveness of the proposed transceiver design.

Original language	English
Title of host publication	2019 IEEE Globecom Workshops, GC Wkshps 2019 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728109602
DOIs	https://doi.org/10.1109/GCWkshps45667.2019.9024576
Publication status	Published - 2019 Dec
Event	2019 IEEE Globecom Workshops, GC Wkshps 2019 - Waikoloa, United States Duration: 2019 Dec 9 → 2019 Dec 13

Publication series

Name	2019 IEEE Globecom Workshops, GC Wkshps 2019 - Proceedings

Conference

Conference	2019 IEEE Globecom Workshops, GC Wkshps 2019
Country/Territory	United States
City	Waikoloa
Period	19/12/9 → 19/12/13

Bibliographical note

Funding Information:
This work was supported in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2019R1F1A1060648) and in part by Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (2016-0-00208, High Accurate Positioning Enabled MIMO Transmission and Network Technologies for Next 5G-V2X (vehicleto-everything) Services).

Funding Information:
This work was supported in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2019R1F1A1060648) and in part by Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (2016-0-00208, High Accurate Positioning Enabled MIMO Transmission and Network Technologies for Next 5G-V2X (vehicle-to-everything) Services).

Publisher Copyright:
© 2019 IEEE.

ASJC Scopus subject areas

Computer Networks and Communications
Hardware and Architecture
Software
Control and Optimization

Access to Document

10.1109/GCWkshps45667.2019.9024576

Cite this

Deep learning-aided binary visible light communication systems. / Lee, Hoon; Quek, Tony Q.S.; Lee, Sang Hyun.
2019 IEEE Globecom Workshops, GC Wkshps 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. 9024576 (2019 IEEE Globecom Workshops, GC Wkshps 2019 - Proceedings).

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

Lee, H, Quek, TQS & Lee, SH 2019, Deep learning-aided binary visible light communication systems. in 2019 IEEE Globecom Workshops, GC Wkshps 2019 - Proceedings., 9024576, 2019 IEEE Globecom Workshops, GC Wkshps 2019 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2019 IEEE Globecom Workshops, GC Wkshps 2019, Waikoloa, United States, 19/12/9. https://doi.org/10.1109/GCWkshps45667.2019.9024576

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title = "Deep learning-aided binary visible light communication systems",

abstract = "This paper investigates a deep learning (DL) method for on-off keying (OOK) based visible light communication (VLC) systems where a lighting emitting diode transmits binary optical pulses to a receiver. Universal dimming abilities are considered such that the VLC transceiver meets arbitrary dimming requirement of external users. This poses a combinatorial formulation optimizing binary codewords under multiple dimming constraints. To tackle this, DL techniques are employed to design an OOK encoder-decoder pair over noisy optical channels. For universal dimming support, the training of the DL-based VLC transceiver turns out to be a constrained training problem with multiple dimming constraints. This paper employs a dual formulation to develop a constrained training strategy. Numerical results show the effectiveness of the proposed transceiver design.",

author = "Hoon Lee and Quek, {Tony Q.S.} and Lee, {Sang Hyun}",

note = "Funding Information: This work was supported in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2019R1F1A1060648) and in part by Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (2016-0-00208, High Accurate Positioning Enabled MIMO Transmission and Network Technologies for Next 5G-V2X (vehicleto-everything) Services). Funding Information: This work was supported in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2019R1F1A1060648) and in part by Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (2016-0-00208, High Accurate Positioning Enabled MIMO Transmission and Network Technologies for Next 5G-V2X (vehicle-to-everything) Services). Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE Globecom Workshops, GC Wkshps 2019 ; Conference date: 09-12-2019 Through 13-12-2019",

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N2 - This paper investigates a deep learning (DL) method for on-off keying (OOK) based visible light communication (VLC) systems where a lighting emitting diode transmits binary optical pulses to a receiver. Universal dimming abilities are considered such that the VLC transceiver meets arbitrary dimming requirement of external users. This poses a combinatorial formulation optimizing binary codewords under multiple dimming constraints. To tackle this, DL techniques are employed to design an OOK encoder-decoder pair over noisy optical channels. For universal dimming support, the training of the DL-based VLC transceiver turns out to be a constrained training problem with multiple dimming constraints. This paper employs a dual formulation to develop a constrained training strategy. Numerical results show the effectiveness of the proposed transceiver design.

AB - This paper investigates a deep learning (DL) method for on-off keying (OOK) based visible light communication (VLC) systems where a lighting emitting diode transmits binary optical pulses to a receiver. Universal dimming abilities are considered such that the VLC transceiver meets arbitrary dimming requirement of external users. This poses a combinatorial formulation optimizing binary codewords under multiple dimming constraints. To tackle this, DL techniques are employed to design an OOK encoder-decoder pair over noisy optical channels. For universal dimming support, the training of the DL-based VLC transceiver turns out to be a constrained training problem with multiple dimming constraints. This paper employs a dual formulation to develop a constrained training strategy. Numerical results show the effectiveness of the proposed transceiver design.

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Deep learning-aided binary visible light communication systems

Abstract

Publication series

Conference

Bibliographical note

ASJC Scopus subject areas

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