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Lookup NU author(s): Dr Paul HaighORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2013 IEEE.In optical camera communication (OCC) systems leverage on the use of commercial off-the-shelf image sensors to perceive the spatial and temporal variation of light intensity to enable data transmission. However, the transmission data rate is mainly limited by the exposure time and the frame rate of the camera. In addition, the camera's sampling will introduce intersymbol interference (ISI), which will degrade the system performance. In this paper, an artificial neural network (ANN)-based equaliser with the adaptive algorithm is employed for the first time in the field of OCC to mitigate ISI and therefore increase the data rate. Unlike other communication systems, training of the ANN network in OCC is done only once in a lifetime for a range of different exposure time and the network can be stored with a look-up table. The proposed system is theoretically investigated and experimentally evaluated. The results record the highest bit rate for OCC using a single LED source and the Manchester line code (MLC) non-return to zero (NRZ) encoded signal. It also demonstrates 2 to 9 times improved bandwidth depending on the exposure times where the system's bit error rate is below the forward error correction limit.
Author(s): Younus OI, Bani Hassan N, Ghassemlooy Z, Haigh PA, Zvanovec S, Alves LN, Le Minh HL
Publication type: Article
Publication status: Published
Journal: IEEE Access
Year: 2020
Volume: 8
Pages: 42656-42665
Online publication date: 28/02/2020
Acceptance date: 21/02/2020
Date deposited: 28/05/2020
ISSN (electronic): 2169-3536
Publisher: Institute of Electrical and Electronics Engineers Inc.
URL: https://doi.org/10.1109/ACCESS.2020.2976537
DOI: 10.1109/ACCESS.2020.2976537
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