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 journalArticlepeer-review


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 languageEnglish
Article number128741
Number of pages9
JournalOptics Communications
Early online date8 Jul 2022
Publication statusPublished - 1 Dec 2022


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