Modeling and Mitigating LED Nonlinearity using Nonlinear ARX model with Wavelet Networks

Jundao Mo, Xiong Deng, Wenxiang Fan, Yinan Niu, Yixian Dong, Guofu Zhou, Jean Paul Linnartz

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

Samenvatting

In this paper, a nonlinear autoregressive exogenous (NARX) model with a wavelet network is applied to model and compensate the nonlinearity of the LED in Visible Light Communications (VLC). The NARX model shows the ability to accurately describe the response of the LED. PAM-4 signal with a symbol rate of 5 Msym/s is used to demonstrate the performance of the NARX adaptive compensator. The eyediagrams show that this compensator can substantially improve the distorted signal. The complexity of the NARX adaptive compensator is relatively low, with only 15 units. This also facilitates the adaptive parameters updating process due to the small number of parameters in the NARX adaptive compensator.

Originele taal-2Engels
Titel2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA)
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's7-11
Aantal pagina's5
ISBN van elektronische versie9781665422482
DOI's
StatusGepubliceerd - 30 aug. 2021
Evenement16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021 - Chengdu, China
Duur: 1 aug. 20214 aug. 2021
Congresnummer: 16

Congres

Congres16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021
Land/RegioChina
StadChengdu
Periode1/08/214/08/21

Bibliografische nota

Publisher Copyright:
© 2021 IEEE.

Financiering

This work was supported by the National Natural Science Foundation of China under Grant 62001174, Science and Technology Program of Guangzhou (No. 2019050001), Fundamental Research Funds for the Central Universities under Grant A0920502052101-127188, and by EU H2020 Project under Grant ELIOT 825651, Guangdong Provincial Key Laboratory of Optical Information Materials and Technology (No. 2017B030301007), MOE International Laboratory for Optical Information Technologies and the 111 Project.

FinanciersFinanciernummer
Guangdong Provincial Key Laboratory of Optical Information Materials and Technology2017B030301007
H2020 ProjectELIOT 825651
European Union’s Horizon Europe research and innovation programme825651
National Natural Science Foundation of China62001174
Ministry of Education of the People's Republic of China
Guangzhou Science and Technology Program key projects2019050001
Fundamental Research Funds for the Central UniversitiesA0920502052101-127188

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