Deep-Learning-Based Channel Estimation for Multi-wavelength Visible Light Communication System

Zhao Ma; Peiyu Jia; Dahai Han; Min Zhang; Zabih Ghassemlooy; Liqiang Wang

doi:10.1109/wasowc54657.2022.9798444

Deep-Learning-Based Channel Estimation for Multi-wavelength Visible Light Communication System

Zhao Ma, Peiyu Jia, Dahai Han, Min Zhang, Zabih Ghassemlooy, Liqiang Wang

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

1 Citation (Scopus)

Abstract

This paper presents a method for channel modeling of multi-wavelength Visible Light Communication (VLC) system, and compares the effects of long short-term memory (LSTM), gated recurrent unit (GRU), sparse autoencoder-s (SAEs) algorithms in channel modeling. The results show that the SAEs algorithm fits the best with a mean square error of only 3 ×10-6. Besides, we construct the multi-wavelength channel of the RGB tricolor LED light source and model it. Finally, after analyzing the influence of many factors on the channel, it is concluded that the modeling effect of the short-wavelength signal source is the best.

Original language	English
Title of host publication	2022 4th West Asian Symposium on Optical and Millimeter-wave Wireless Communications (WASOWC)
Publisher	IEEE
Number of pages	4
ISBN (Electronic)	9781665409131
ISBN (Print)	9781665409148
DOIs	https://doi.org/10.1109/wasowc54657.2022.9798444
Publication status	Published - 12 May 2022
Event	2022 4th West Asian Symposium on Optical and Millimeter-wave Wireless Communications - University of Tabriz, Tabriz, Iran, Islamic Republic of Duration: 12 May 2022 → 13 May 2022 https://wasowc2022.tabrizu.ac.ir/en

Conference

Conference	2022 4th West Asian Symposium on Optical and Millimeter-wave Wireless Communications
Abbreviated title	WASOWC 2022
Country/Territory	Iran, Islamic Republic of
City	Tabriz
Period	12/05/22 → 13/05/22
Internet address	https://wasowc2022.tabrizu.ac.ir/en

Keywords

channel modeling
deep learning
multi-wavelength communication

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10.1109/wasowc54657.2022.9798444

Cite this

@inproceedings{30e185b7dad3458b9b3e4957558d99fc,

title = "Deep-Learning-Based Channel Estimation for Multi-wavelength Visible Light Communication System",

abstract = "This paper presents a method for channel modeling of multi-wavelength Visible Light Communication (VLC) system, and compares the effects of long short-term memory (LSTM), gated recurrent unit (GRU), sparse autoencoder-s (SAEs) algorithms in channel modeling. The results show that the SAEs algorithm fits the best with a mean square error of only 3 ×10-6. Besides, we construct the multi-wavelength channel of the RGB tricolor LED light source and model it. Finally, after analyzing the influence of many factors on the channel, it is concluded that the modeling effect of the short-wavelength signal source is the best.",

keywords = "channel modeling, deep learning, multi-wavelength communication",

author = "Zhao Ma and Peiyu Jia and Dahai Han and Min Zhang and Zabih Ghassemlooy and Liqiang Wang",

year = "2022",

month = may,

day = "12",

doi = "10.1109/wasowc54657.2022.9798444",

language = "English",

isbn = "9781665409148",

booktitle = "2022 4th West Asian Symposium on Optical and Millimeter-wave Wireless Communications (WASOWC)",

publisher = "IEEE",

address = "United States",

note = "2022 4th West Asian Symposium on Optical and Millimeter-wave Wireless Communications , WASOWC 2022 ; Conference date: 12-05-2022 Through 13-05-2022",

url = "https://wasowc2022.tabrizu.ac.ir/en",

}

Ma, Z, Jia, P, Han, D, Zhang, M, Ghassemlooy, Z & Wang, L 2022, Deep-Learning-Based Channel Estimation for Multi-wavelength Visible Light Communication System. in 2022 4th West Asian Symposium on Optical and Millimeter-wave Wireless Communications (WASOWC). IEEE, 2022 4th West Asian Symposium on Optical and Millimeter-wave Wireless Communications , Tabriz, Iran, Islamic Republic of, 12/05/22. https://doi.org/10.1109/wasowc54657.2022.9798444

TY - GEN

T1 - Deep-Learning-Based Channel Estimation for Multi-wavelength Visible Light Communication System

AU - Ma, Zhao

AU - Jia, Peiyu

AU - Han, Dahai

AU - Zhang, Min

AU - Ghassemlooy, Zabih

AU - Wang, Liqiang

PY - 2022/5/12

Y1 - 2022/5/12

N2 - This paper presents a method for channel modeling of multi-wavelength Visible Light Communication (VLC) system, and compares the effects of long short-term memory (LSTM), gated recurrent unit (GRU), sparse autoencoder-s (SAEs) algorithms in channel modeling. The results show that the SAEs algorithm fits the best with a mean square error of only 3 ×10-6. Besides, we construct the multi-wavelength channel of the RGB tricolor LED light source and model it. Finally, after analyzing the influence of many factors on the channel, it is concluded that the modeling effect of the short-wavelength signal source is the best.

AB - This paper presents a method for channel modeling of multi-wavelength Visible Light Communication (VLC) system, and compares the effects of long short-term memory (LSTM), gated recurrent unit (GRU), sparse autoencoder-s (SAEs) algorithms in channel modeling. The results show that the SAEs algorithm fits the best with a mean square error of only 3 ×10-6. Besides, we construct the multi-wavelength channel of the RGB tricolor LED light source and model it. Finally, after analyzing the influence of many factors on the channel, it is concluded that the modeling effect of the short-wavelength signal source is the best.

KW - channel modeling

KW - deep learning

KW - multi-wavelength communication

UR - https://www.scopus.com/pages/publications/85134264999

U2 - 10.1109/wasowc54657.2022.9798444

DO - 10.1109/wasowc54657.2022.9798444

M3 - Conference contribution

SN - 9781665409148

BT - 2022 4th West Asian Symposium on Optical and Millimeter-wave Wireless Communications (WASOWC)

PB - IEEE

T2 - 2022 4th West Asian Symposium on Optical and Millimeter-wave Wireless Communications

Y2 - 12 May 2022 through 13 May 2022

ER -

Deep-Learning-Based Channel Estimation for Multi-wavelength Visible Light Communication System

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Keywords

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