Performance improvement of a CAP VLC system employing a deep learning-based post equalizer

Atiyeh Pouralizadeh; Gholamreza Baghersalimi; Zabih Ghassemlooy; Mahdi Nassiri

doi:10.1016/j.optcom.2022.128741

Performance improvement of a CAP VLC system employing a deep learning-based post equalizer

Atiyeh Pouralizadeh, Gholamreza Baghersalimi^*, Zabih Ghassemlooy, Mahdi Nassiri

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

Abstract

We propose in this paper a carrier-less amplitude and phase visible light communications (VLC) system with deep learning (DL)-based post-equalizer (EQ) to significantly increase the transmission data rate. The proposed system is analyzed for various conditions including modulation order, transmitted signal bandwidth, and non-line of sight VLC channel. Results show that the highest data rate and spectral efficiency of 100 Mb/s and 4.67 b/s/Hz are achieved for the modulation order and signal bandwidth of 64 and 25 MHz, respectively. In addition, we compare the performance and complexity of the proposed system with different types of EQs including least mean square and Volterra series. The study shows the DL-based EQ is qualified to mitigate mixed linear and nonlinear impairments by providing improved bit error rate performance compared to the other EQs for all modulation orders and the transmitted signal bandwidth.

Original language	English
Article number	128741
Number of pages	9
Journal	Optics Communications
Volume	524
Early online date	8 Jul 2022
DOIs	https://doi.org/10.1016/j.optcom.2022.128741
Publication status	Published - 1 Dec 2022

Keywords

Carrier-less amplitude and phase (CAP) modulation
Deep learning (DL)
Visible light communications (VLC)

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10.1016/j.optcom.2022.128741

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title = "Performance improvement of a CAP VLC system employing a deep learning-based post equalizer",

abstract = "We propose in this paper a carrier-less amplitude and phase visible light communications (VLC) system with deep learning (DL)-based post-equalizer (EQ) to significantly increase the transmission data rate. The proposed system is analyzed for various conditions including modulation order, transmitted signal bandwidth, and non-line of sight VLC channel. Results show that the highest data rate and spectral efficiency of 100 Mb/s and 4.67 b/s/Hz are achieved for the modulation order and signal bandwidth of 64 and 25 MHz, respectively. In addition, we compare the performance and complexity of the proposed system with different types of EQs including least mean square and Volterra series. The study shows the DL-based EQ is qualified to mitigate mixed linear and nonlinear impairments by providing improved bit error rate performance compared to the other EQs for all modulation orders and the transmitted signal bandwidth.",

keywords = "Carrier-less amplitude and phase (CAP) modulation, Deep learning (DL), Visible light communications (VLC)",

author = "Atiyeh Pouralizadeh and Gholamreza Baghersalimi and Zabih Ghassemlooy and Mahdi Nassiri",

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T1 - Performance improvement of a CAP VLC system employing a deep learning-based post equalizer

AU - Pouralizadeh, Atiyeh

AU - Baghersalimi, Gholamreza

AU - Ghassemlooy, Zabih

AU - Nassiri, Mahdi

PY - 2022/12/1

Y1 - 2022/12/1

N2 - We propose in this paper a carrier-less amplitude and phase visible light communications (VLC) system with deep learning (DL)-based post-equalizer (EQ) to significantly increase the transmission data rate. The proposed system is analyzed for various conditions including modulation order, transmitted signal bandwidth, and non-line of sight VLC channel. Results show that the highest data rate and spectral efficiency of 100 Mb/s and 4.67 b/s/Hz are achieved for the modulation order and signal bandwidth of 64 and 25 MHz, respectively. In addition, we compare the performance and complexity of the proposed system with different types of EQs including least mean square and Volterra series. The study shows the DL-based EQ is qualified to mitigate mixed linear and nonlinear impairments by providing improved bit error rate performance compared to the other EQs for all modulation orders and the transmitted signal bandwidth.

AB - We propose in this paper a carrier-less amplitude and phase visible light communications (VLC) system with deep learning (DL)-based post-equalizer (EQ) to significantly increase the transmission data rate. The proposed system is analyzed for various conditions including modulation order, transmitted signal bandwidth, and non-line of sight VLC channel. Results show that the highest data rate and spectral efficiency of 100 Mb/s and 4.67 b/s/Hz are achieved for the modulation order and signal bandwidth of 64 and 25 MHz, respectively. In addition, we compare the performance and complexity of the proposed system with different types of EQs including least mean square and Volterra series. The study shows the DL-based EQ is qualified to mitigate mixed linear and nonlinear impairments by providing improved bit error rate performance compared to the other EQs for all modulation orders and the transmitted signal bandwidth.

KW - Carrier-less amplitude and phase (CAP) modulation

KW - Deep learning (DL)

KW - Visible light communications (VLC)

UR - https://www.scopus.com/pages/publications/85134853484

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DO - 10.1016/j.optcom.2022.128741

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VL - 524

JO - Optics Communications

JF - Optics Communications

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Performance improvement of a CAP VLC system employing a deep learning-based post equalizer

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Keywords

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