The Utilization of Artificial Neural Network Equalizer in Optical Camera Communications

Othman Isam Younus*, Navid Bani Hassan, Zabih Ghassemlooy, Stanislav Zvánovec, Luis Nero Alves, Hoa Le-Minh

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)
18 Downloads (Pure)


In this paper, we propose and validate an artificial neural network-based equalizer for the constant power 4-level pulse amplitude modulation in an optical camera communications system. We introduce new terminology to measure the quality of the communications link in terms of the number of row pixels per symbol , which allows a fair comparison considering the progress made in the development of the current image sensors in terms of the frame rates and the resolutions of each frame. Using the proposed equalizer, we experimentally demonstrate a non-flickering system using a single light-emitting diode (LED) with of 20 and 30 pixels/symbol for the unequalized and equalized systems, respectively. Potential transmission rates of up to 18.6 and 24.4 kbps are achieved with and without the equalization, respectively. The quality of the received signal is assessed using the eye-diagram opening and its linearity and the bit error rate performance. An acceptable bit error rate (below the forward error correction limit) and an improvement of ~66% in the eye linearity are achieved using a single LED and a typical commercial camera with equalization.
Original languageEnglish
Article number2826
Number of pages17
Issue number8
Publication statusPublished - 16 Apr 2021


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