Binary signaling design for visible light communication: a deep learning framework

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

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

This paper develops a deep learning framework for the design of on-o keying (OOK) based binary signaling transceiver in dimmable visible light communication (VLC) systems. The dimming support for the OOK optical signal is achieved by adjusting the number of ones in a binary codeword, which boils down to a combinatorial design problem for the codebook of a constant weight code (CWC) over signal-dependent noise channels. To tackle this challenge, we employ an autoencoder (AE) approach to learn a neural network of the encoder-decoder pair that reconstructs the output identical to an input. In addition, optical channel layers and binarization techniques are introduced to reflect the physical and discrete nature of the OOK-based VLC systems. The VLC transceiver is designed and optimized via the end-to-end training procedure for the AE. Numerical results verify that the proposed transceiver performs better than baseline CWC schemes.

Original languageEnglish
Pages (from-to)18131-18142
Number of pages12
JournalOptics Express
Volume26
Issue number14
DOIs
Publication statusPublished - 2018 Jul 9

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keying
learning
optical communication
transmitter receivers
telecommunication
channel noise
dimming
decoders
coders
education
adjusting
output

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics

Cite this

Binary signaling design for visible light communication : a deep learning framework. / Lee, Hoon; Lee, Inkyu; Quek, Tony Q.S.; Lee, Sang Hyun.

In: Optics Express, Vol. 26, No. 14, 09.07.2018, p. 18131-18142.

Research output: Contribution to journalArticle

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