Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/85325
Title: | LED nonlinearity estimation and compensation in VLC systems using probabilistic bayesian learning | Authors: | Chen, Chen Deng, Xiong Yang, Yanbing Du, Pengfei Yang, Helin Zhao, Lifan |
Keywords: | Nonlinearity Estimation and Compensation Engineering::Electrical and electronic engineering Light Emitting Diode |
Issue Date: | 2019 | Source: | Chen, C., Deng, X., Yang, Y., Du, P., Yang, H., & Zhao, L. (2019). LED Nonlinearity Estimation and Compensation in VLC Systems Using Probabilistic Bayesian Learning. Applied Sciences, 9(13), 2711-. doi:10.3390/app9132711 | Series/Report no.: | Applied Sciences | Abstract: | In this paper, we propose and evaluate a novel light-emitting diode (LED) nonlinearity estimation and compensation scheme using probabilistic Bayesian learning (PBL) for spectral-efficient visible light communication (VLC) systems. The nonlinear power-current curve of the LED transmitter can be accurately estimated by exploiting PBL regression and hence the adverse effect of LED nonlinearity can be efficiently compensated. Simulation results show that, in a 80-Mbit/s orthogonal frequency division multiplexing (OFDM)-based nonlinear VLC system, comparable bit-error rate (BER) performance can be achieved by the conventional time domain averaging (TDA)-based LED nonlinearity mitigation scheme with totally 20 training symbols (TSs) and the proposed PBL-based scheme with only a single TS. Therefore, compared with the conventional TDA scheme, the proposed PBL-based scheme can substantially reduce the required training overhead and hence greatly improve the overall spectral efficiency of bandlimited VLC systems. It is also shown that the PBL-based LED nonlinearity estimation and compensation scheme is computational efficient for the implementation in practical VLC systems. | URI: | https://hdl.handle.net/10356/85325 http://hdl.handle.net/10220/49806 |
ISSN: | 2076-3417 | DOI: | 10.3390/app9132711 | Schools: | School of Electrical and Electronic Engineering | Rights: | © 2019 by the Authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | EEE Journal Articles |
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LED Nonlinearity Estimation and Compensation in VLC Systems Using Probabilistic Bayesian Learning.pdf | 1.98 MB | Adobe PDF | View/Open |
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