Demonstration of a low-complexity memory-polynomial-aided neural network equalizer for CAP visible-light communication with superluminescent diode

Visible-light communication (VLC) stands as a promising component of the future communication network by providing high-capacity, low-latency, and high-security wireless communication. Superluminescent diode (SLD) is proposed as a new light emitter in the VLC system due to its properties of droop-fr...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Hu Fangchen, Holguin-Lerma Jorge A., Mao Yuan, Zou Peng, Shen Chao, Ng Tien Khee, Ooi Boon S., Chi Nan
Formato:	article
Lenguaje:	EN
Publicado:	Institue of Optics and Electronics, Chinese Academy of Sciences 2020
Materias:	superluminescent diode visible-light communication neural network Optics. Light QC350-467
Acceso en línea:	https://doaj.org/article/aa8c947510b24f89bcc10ccf32d0f38d
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:aa8c947510b24f89bcc10ccf32d0f38d
record_format	dspace
spelling	oai:doaj.org-article:aa8c947510b24f89bcc10ccf32d0f38d2021-11-10T10:02:42ZDemonstration of a low-complexity memory-polynomial-aided neural network equalizer for CAP visible-light communication with superluminescent diode2096-457910.29026/oea.2020.200009https://doaj.org/article/aa8c947510b24f89bcc10ccf32d0f38d2020-08-01T00:00:00Zhttp://www.oejournal.org/article/doi/10.29026/oea.2020.200009https://doaj.org/toc/2096-4579Visible-light communication (VLC) stands as a promising component of the future communication network by providing high-capacity, low-latency, and high-security wireless communication. Superluminescent diode (SLD) is proposed as a new light emitter in the VLC system due to its properties of droop-free emission, high optical power density, and low speckle-noise. In this paper, we analyze a VLC system based on SLD, demonstrating effective implementation of carrierless amplitude and phase modulation (CAP). We create a low-complexity memory-polynomial-aided neural network (MPANN) to replace the traditional finite impulse response (FIR) post-equalization filters of CAP, leading to significant mitigation of the linear and nonlinear distortion of the VLC channel. The MPANN shows a gain in Q factor of up to 2.7 dB higher than other equalizers, and more than four times lower complexity than a standard deep neural network (DNN), hence, the proposed MPANN opens a pathway for the next generation of robust and efficient neural network equalizers in VLC. We experimentally demonstrate a proof-of-concept 2.95-Gbit/s transmission using MPANN-aided CAP with 16-quadrature amplitude modulation (16-QAM) through a 30-cm channel based on the 442-nm blue SLD emitter.Hu FangchenHolguin-Lerma Jorge A.Mao YuanZou PengShen ChaoNg Tien KheeOoi Boon S.Chi NanInstitue of Optics and Electronics, Chinese Academy of Sciencesarticlesuperluminescent diodevisible-light communicationneural networkOptics. LightQC350-467ENOpto-Electronic Advances, Vol 3, Iss 8, Pp 200009-1-200009-11 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	superluminescent diode visible-light communication neural network Optics. Light QC350-467
spellingShingle	superluminescent diode visible-light communication neural network Optics. Light QC350-467 Hu Fangchen Holguin-Lerma Jorge A. Mao Yuan Zou Peng Shen Chao Ng Tien Khee Ooi Boon S. Chi Nan Demonstration of a low-complexity memory-polynomial-aided neural network equalizer for CAP visible-light communication with superluminescent diode
description	Visible-light communication (VLC) stands as a promising component of the future communication network by providing high-capacity, low-latency, and high-security wireless communication. Superluminescent diode (SLD) is proposed as a new light emitter in the VLC system due to its properties of droop-free emission, high optical power density, and low speckle-noise. In this paper, we analyze a VLC system based on SLD, demonstrating effective implementation of carrierless amplitude and phase modulation (CAP). We create a low-complexity memory-polynomial-aided neural network (MPANN) to replace the traditional finite impulse response (FIR) post-equalization filters of CAP, leading to significant mitigation of the linear and nonlinear distortion of the VLC channel. The MPANN shows a gain in Q factor of up to 2.7 dB higher than other equalizers, and more than four times lower complexity than a standard deep neural network (DNN), hence, the proposed MPANN opens a pathway for the next generation of robust and efficient neural network equalizers in VLC. We experimentally demonstrate a proof-of-concept 2.95-Gbit/s transmission using MPANN-aided CAP with 16-quadrature amplitude modulation (16-QAM) through a 30-cm channel based on the 442-nm blue SLD emitter.
format	article
author	Hu Fangchen Holguin-Lerma Jorge A. Mao Yuan Zou Peng Shen Chao Ng Tien Khee Ooi Boon S. Chi Nan
author_facet	Hu Fangchen Holguin-Lerma Jorge A. Mao Yuan Zou Peng Shen Chao Ng Tien Khee Ooi Boon S. Chi Nan
author_sort	Hu Fangchen
title	Demonstration of a low-complexity memory-polynomial-aided neural network equalizer for CAP visible-light communication with superluminescent diode
title_short	Demonstration of a low-complexity memory-polynomial-aided neural network equalizer for CAP visible-light communication with superluminescent diode
title_full	Demonstration of a low-complexity memory-polynomial-aided neural network equalizer for CAP visible-light communication with superluminescent diode
title_fullStr	Demonstration of a low-complexity memory-polynomial-aided neural network equalizer for CAP visible-light communication with superluminescent diode
title_full_unstemmed	Demonstration of a low-complexity memory-polynomial-aided neural network equalizer for CAP visible-light communication with superluminescent diode
title_sort	demonstration of a low-complexity memory-polynomial-aided neural network equalizer for cap visible-light communication with superluminescent diode
publisher	Institue of Optics and Electronics, Chinese Academy of Sciences
publishDate	2020
url	https://doaj.org/article/aa8c947510b24f89bcc10ccf32d0f38d
work_keys_str_mv	AT hufangchen demonstrationofalowcomplexitymemorypolynomialaidedneuralnetworkequalizerforcapvisiblelightcommunicationwithsuperluminescentdiode AT holguinlermajorgea demonstrationofalowcomplexitymemorypolynomialaidedneuralnetworkequalizerforcapvisiblelightcommunicationwithsuperluminescentdiode AT maoyuan demonstrationofalowcomplexitymemorypolynomialaidedneuralnetworkequalizerforcapvisiblelightcommunicationwithsuperluminescentdiode AT zoupeng demonstrationofalowcomplexitymemorypolynomialaidedneuralnetworkequalizerforcapvisiblelightcommunicationwithsuperluminescentdiode AT shenchao demonstrationofalowcomplexitymemorypolynomialaidedneuralnetworkequalizerforcapvisiblelightcommunicationwithsuperluminescentdiode AT ngtienkhee demonstrationofalowcomplexitymemorypolynomialaidedneuralnetworkequalizerforcapvisiblelightcommunicationwithsuperluminescentdiode AT ooiboons demonstrationofalowcomplexitymemorypolynomialaidedneuralnetworkequalizerforcapvisiblelightcommunicationwithsuperluminescentdiode AT chinan demonstrationofalowcomplexitymemorypolynomialaidedneuralnetworkequalizerforcapvisiblelightcommunicationwithsuperluminescentdiode
_version_	1718440125689495552

Demonstration of a low-complexity memory-polynomial-aided neural network equalizer for CAP visible-light communication with superluminescent diode

Ejemplares similares