IEICE TRANSACTIONS on Electronics
MIMO Systems with Neural Networks in OFDM-Based WDM Visible Light Communications
Summary :
In this paper, we describe a wavelength-division multiplexing visible-light communication (VLC) system using two colored light-emitting diodes (LEDs) with similar emission wavelengths. A multi-input multi-output signal-separation method using a neural network is proposed to cancel the optical cross chatter caused by the spectral overlap of LEDs. The experimental results demonstrate that signal separation using neural networks can be achieved in wavelength-multiplexed VLC systems with a bit error rate of less than 3.8×10-3 (forward error correction limit). Furthermore, the simulation results reveal that the carrier-to-noise ratio (CNR) is improved by 2dB for the successive interference canceller (SIC) compared to the zero-forcing method.
- Publication
- IEICE TRANSACTIONS on Electronics Vol.E106-C No.11 pp.727-730
- Publication Date
- 2023/11/01
- Publicized
- 2023/05/12
- Online ISSN
- 1745-1353
- DOI
- 10.1587/transele.2023MMS0003
- Type of Manuscript
- BRIEF PAPER
- Category
Authors
Naoki UMEZAWA
Kyoto Institute of Techonology
Saeko OSHIBA
Kyoto Institute of Techonology
Keyword
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Naoki UMEZAWA, Saeko OSHIBA, "MIMO Systems with Neural Networks in OFDM-Based WDM Visible Light Communications" in IEICE TRANSACTIONS on Electronics,
vol. E106-C, no. 11, pp. 727-730, November 2023, doi: 10.1587/transele.2023MMS0003.
Abstract: In this paper, we describe a wavelength-division multiplexing visible-light communication (VLC) system using two colored light-emitting diodes (LEDs) with similar emission wavelengths. A multi-input multi-output signal-separation method using a neural network is proposed to cancel the optical cross chatter caused by the spectral overlap of LEDs. The experimental results demonstrate that signal separation using neural networks can be achieved in wavelength-multiplexed VLC systems with a bit error rate of less than 3.8×10-3 (forward error correction limit). Furthermore, the simulation results reveal that the carrier-to-noise ratio (CNR) is improved by 2dB for the successive interference canceller (SIC) compared to the zero-forcing method.
URL: https://global.ieice.org/en_transactions/electronics/10.1587/transele.2023MMS0003/_p
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@ARTICLE{e106-c_11_727,
author={Naoki UMEZAWA, Saeko OSHIBA, },
journal={IEICE TRANSACTIONS on Electronics},
title={MIMO Systems with Neural Networks in OFDM-Based WDM Visible Light Communications},
year={2023},
volume={E106-C},
number={11},
pages={727-730},
abstract={In this paper, we describe a wavelength-division multiplexing visible-light communication (VLC) system using two colored light-emitting diodes (LEDs) with similar emission wavelengths. A multi-input multi-output signal-separation method using a neural network is proposed to cancel the optical cross chatter caused by the spectral overlap of LEDs. The experimental results demonstrate that signal separation using neural networks can be achieved in wavelength-multiplexed VLC systems with a bit error rate of less than 3.8×10-3 (forward error correction limit). Furthermore, the simulation results reveal that the carrier-to-noise ratio (CNR) is improved by 2dB for the successive interference canceller (SIC) compared to the zero-forcing method.},
keywords={},
doi={10.1587/transele.2023MMS0003},
ISSN={1745-1353},
month={November},}
Copy
TY - JOUR
TI - MIMO Systems with Neural Networks in OFDM-Based WDM Visible Light Communications
T2 - IEICE TRANSACTIONS on Electronics
SP - 727
EP - 730
AU - Naoki UMEZAWA
AU - Saeko OSHIBA
PY - 2023
DO - 10.1587/transele.2023MMS0003
JO - IEICE TRANSACTIONS on Electronics
SN - 1745-1353
VL - E106-C
IS - 11
JA - IEICE TRANSACTIONS on Electronics
Y1 - November 2023
AB - In this paper, we describe a wavelength-division multiplexing visible-light communication (VLC) system using two colored light-emitting diodes (LEDs) with similar emission wavelengths. A multi-input multi-output signal-separation method using a neural network is proposed to cancel the optical cross chatter caused by the spectral overlap of LEDs. The experimental results demonstrate that signal separation using neural networks can be achieved in wavelength-multiplexed VLC systems with a bit error rate of less than 3.8×10-3 (forward error correction limit). Furthermore, the simulation results reveal that the carrier-to-noise ratio (CNR) is improved by 2dB for the successive interference canceller (SIC) compared to the zero-forcing method.
ER -
English
