Data-driven state estimation for light-emitting diode underwater optical communication

Yingquan Li; Zhenwen Liang; Ibrahima N'Doye; Xiangliang Zhang; Mohamed Slim Alouini; Taous Meriem Laleg-Kirati

doi:10.1016/j.ifacol.2023.10.408

Data-driven state estimation for light-emitting diode underwater optical communication

Yingquan Li, Zhenwen Liang, Ibrahima N'Doye, Xiangliang Zhang, Mohamed Slim Alouini, Taous Meriem Laleg-Kirati

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

2 Scopus citations

Abstract

Light-Emitting Diodes (LEDs) based underwater optical wireless communications (UOWCs), a technology with low latency and high data rates, have attracted significant importance for underwater robots. However, maintaining a controlled line of sight link between transmitter and receiver is challenging due to the constant movement of the underlying optical platform caused by the dynamic uncertainties of the LED model and vibration effects. Additionally, the alignment angle required for tracking is not directly measured and has to be estimated. Besides, the light scattering propagates beam pulse in water temporally, resulting in nonlinearities and time-varying underwater optical links with interference and introducing challenges in the estimation problem. In this paper, we address the state estimation problem by designing a Luenberger observer for the LED communication system that provides the angular position and velocity state information involved in the challenges of maintaining a controlled LOS optical wireless communication. In this line, we leverage the power of deep learning-based observer design to estimate the state of the LED communication model online. Simulation results are presented to illustrate the performance of the data-driven LED state estimation.

Original language	English (US)
Title of host publication	IFAC-PapersOnLine
Editors	Hideaki Ishii, Yoshio Ebihara, Jun-ichi Imura, Masaki Yamakita
Publisher	Elsevier B.V.
Pages	9862-9868
Number of pages	7
Edition	2
ISBN (Electronic)	9781713872344
DOIs	https://doi.org/10.1016/j.ifacol.2023.10.408
State	Published - Jul 1 2023
Event	22nd IFAC World Congress - Yokohama, Japan Duration: Jul 9 2023 → Jul 14 2023

Publication series

Name	IFAC-PapersOnLine
Number	2
Volume	56
ISSN (Electronic)	2405-8963

Conference

Conference	22nd IFAC World Congress
Country/Territory	Japan
City	Yokohama
Period	07/9/23 → 07/14/23

Keywords

deep learning algorithm
Light-emitting diode
neural networks
nonlinear systems
observer design
online estimation
underwater optical wireless communication

ASJC Scopus subject areas

Control and Systems Engineering

Access to Document

10.1016/j.ifacol.2023.10.408

Cite this

Li, Y., Liang, Z., N'Doye, I., Zhang, X., Alouini, M. S., & Laleg-Kirati, T. M. (2023). Data-driven state estimation for light-emitting diode underwater optical communication. In H. Ishii, Y. Ebihara, J. Imura, & M. Yamakita (Eds.), IFAC-PapersOnLine (2 ed., pp. 9862-9868). (IFAC-PapersOnLine; Vol. 56, No. 2). Elsevier B.V.. https://doi.org/10.1016/j.ifacol.2023.10.408

@inproceedings{190f2d28070d42989df4cbb984feeff4,

title = "Data-driven state estimation for light-emitting diode underwater optical communication",

abstract = "Light-Emitting Diodes (LEDs) based underwater optical wireless communications (UOWCs), a technology with low latency and high data rates, have attracted significant importance for underwater robots. However, maintaining a controlled line of sight link between transmitter and receiver is challenging due to the constant movement of the underlying optical platform caused by the dynamic uncertainties of the LED model and vibration effects. Additionally, the alignment angle required for tracking is not directly measured and has to be estimated. Besides, the light scattering propagates beam pulse in water temporally, resulting in nonlinearities and time-varying underwater optical links with interference and introducing challenges in the estimation problem. In this paper, we address the state estimation problem by designing a Luenberger observer for the LED communication system that provides the angular position and velocity state information involved in the challenges of maintaining a controlled LOS optical wireless communication. In this line, we leverage the power of deep learning-based observer design to estimate the state of the LED communication model online. Simulation results are presented to illustrate the performance of the data-driven LED state estimation.",

keywords = "deep learning algorithm, Light-emitting diode, neural networks, nonlinear systems, observer design, online estimation, underwater optical wireless communication",

author = "Yingquan Li and Zhenwen Liang and Ibrahima N'Doye and Xiangliang Zhang and Alouini, {Mohamed Slim} and Laleg-Kirati, {Taous Meriem}",

note = "Publisher Copyright: Copyright {\textcopyright} 2023 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/); 22nd IFAC World Congress ; Conference date: 09-07-2023 Through 14-07-2023",

year = "2023",

month = jul,

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doi = "10.1016/j.ifacol.2023.10.408",

language = "English (US)",

series = "IFAC-PapersOnLine",

publisher = "Elsevier B.V.",

number = "2",

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editor = "Hideaki Ishii and Yoshio Ebihara and Jun-ichi Imura and Masaki Yamakita",

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Li, Y, Liang, Z, N'Doye, I, Zhang, X, Alouini, MS & Laleg-Kirati, TM 2023, Data-driven state estimation for light-emitting diode underwater optical communication. in H Ishii, Y Ebihara, J Imura & M Yamakita (eds), IFAC-PapersOnLine. 2 edn, IFAC-PapersOnLine, no. 2, vol. 56, Elsevier B.V., pp. 9862-9868, 22nd IFAC World Congress, Yokohama, Japan, 07/9/23. https://doi.org/10.1016/j.ifacol.2023.10.408

Data-driven state estimation for light-emitting diode underwater optical communication. / Li, Yingquan; Liang, Zhenwen; N'Doye, Ibrahima et al.
IFAC-PapersOnLine. ed. / Hideaki Ishii; Yoshio Ebihara; Jun-ichi Imura; Masaki Yamakita. 2. ed. Elsevier B.V., 2023. p. 9862-9868 (IFAC-PapersOnLine; Vol. 56, No. 2).

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

TY - GEN

T1 - Data-driven state estimation for light-emitting diode underwater optical communication

AU - Li, Yingquan

AU - Liang, Zhenwen

AU - N'Doye, Ibrahima

AU - Zhang, Xiangliang

AU - Alouini, Mohamed Slim

AU - Laleg-Kirati, Taous Meriem

PY - 2023/7/1

Y1 - 2023/7/1

N2 - Light-Emitting Diodes (LEDs) based underwater optical wireless communications (UOWCs), a technology with low latency and high data rates, have attracted significant importance for underwater robots. However, maintaining a controlled line of sight link between transmitter and receiver is challenging due to the constant movement of the underlying optical platform caused by the dynamic uncertainties of the LED model and vibration effects. Additionally, the alignment angle required for tracking is not directly measured and has to be estimated. Besides, the light scattering propagates beam pulse in water temporally, resulting in nonlinearities and time-varying underwater optical links with interference and introducing challenges in the estimation problem. In this paper, we address the state estimation problem by designing a Luenberger observer for the LED communication system that provides the angular position and velocity state information involved in the challenges of maintaining a controlled LOS optical wireless communication. In this line, we leverage the power of deep learning-based observer design to estimate the state of the LED communication model online. Simulation results are presented to illustrate the performance of the data-driven LED state estimation.

AB - Light-Emitting Diodes (LEDs) based underwater optical wireless communications (UOWCs), a technology with low latency and high data rates, have attracted significant importance for underwater robots. However, maintaining a controlled line of sight link between transmitter and receiver is challenging due to the constant movement of the underlying optical platform caused by the dynamic uncertainties of the LED model and vibration effects. Additionally, the alignment angle required for tracking is not directly measured and has to be estimated. Besides, the light scattering propagates beam pulse in water temporally, resulting in nonlinearities and time-varying underwater optical links with interference and introducing challenges in the estimation problem. In this paper, we address the state estimation problem by designing a Luenberger observer for the LED communication system that provides the angular position and velocity state information involved in the challenges of maintaining a controlled LOS optical wireless communication. In this line, we leverage the power of deep learning-based observer design to estimate the state of the LED communication model online. Simulation results are presented to illustrate the performance of the data-driven LED state estimation.

KW - deep learning algorithm

KW - Light-emitting diode

KW - neural networks

KW - nonlinear systems

KW - observer design

KW - online estimation

KW - underwater optical wireless communication

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DO - 10.1016/j.ifacol.2023.10.408

M3 - Conference contribution

AN - SCOPUS:85184961689

T3 - IFAC-PapersOnLine

SP - 9862

EP - 9868

BT - IFAC-PapersOnLine

A2 - Ishii, Hideaki

A2 - Ebihara, Yoshio

A2 - Imura, Jun-ichi

A2 - Yamakita, Masaki

PB - Elsevier B.V.

T2 - 22nd IFAC World Congress

Y2 - 9 July 2023 through 14 July 2023

ER -

Data-driven state estimation for light-emitting diode underwater optical communication

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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