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 language | English |
|---|---|
| Pages (from-to) | 18131-18142 |
| Number of pages | 12 |
| Journal | Optics Express |
| Volume | 26 |
| Issue number | 14 |
| DOIs | |
| Publication status | Published - 2018 Jul 9 |
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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 journal › Article
}
TY - JOUR
T1 - Binary signaling design for visible light communication
T2 - a deep learning framework
AU - Lee, Hoon
AU - Lee, Inkyu
AU - Quek, Tony Q.S.
AU - Lee, Sang Hyun
PY - 2018/7/9
Y1 - 2018/7/9
N2 - 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.
AB - 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.
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U2 - 10.1364/OE.26.018131
DO - 10.1364/OE.26.018131
M3 - Article
C2 - 30114093
AN - SCOPUS:85049596657
VL - 26
SP - 18131
EP - 18142
JO - Optics Express
JF - Optics Express
SN - 1094-4087
IS - 14
ER -