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

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

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.

Original languageEnglish
Title of host publication2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA)
PublisherInstitute of Electrical and Electronics Engineers
Pages7-11
Number of pages5
ISBN (Electronic)9781665422482
DOIs
Publication statusPublished - 30 Aug 2021
Event16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021 - Chengdu, China
Duration: 1 Aug 20214 Aug 2021
Conference number: 16

Conference

Conference16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021
Country/TerritoryChina
CityChengdu
Period1/08/214/08/21

Bibliographical note

Funding Information:
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.

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