1-D array of silicon nitride grating couplers for visible light communications

2016 ◽  
Author(s):  
Shahryar Sabouri ◽  
Meysam Namdari ◽  
Seyedreza Hosseini ◽  
Kambiz Jamshidi
Keyword(s):  
Silicon Nitride ◽  
Visible Light ◽  
Visible Light Communications ◽  
Grating Couplers

scholarly journals A Relay-Assisted Vehicular Visible Light Communications Network

2020 ◽  
Author(s):  
Elizabeth Eso ◽  
Petr Pesek ◽  
Petr Chvojka ◽  
Zabih Ghassemlooy ◽  
Stanislav Zvanovec ◽  
...  
Keyword(s):  
Visible Light ◽  
Visible Light Communications ◽  
Communications Network

Space-Time Constellation for MU-MISO Dimmable Visible Light Communications

2021 ◽  
pp. 1-1
Author(s):  
Lin Li ◽  
Ru-Han Chen ◽  
Yan-Yu Zhang ◽  
Jia-Ning Guo ◽  
Jian Zhang
Keyword(s):  
Visible Light ◽  
Space Time ◽  
Visible Light Communications

scholarly journals An ANN-Based Adaptive Predistorter for LED Nonlinearity in Indoor Visible Light Communications

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 948
Author(s):  
Jenn-Kaie Lain ◽  
Yan-He Chen
Keyword(s):  
Visible Light ◽  
Light Emitting Diode ◽  
Optical Power ◽  
Visible Light Communication ◽  
Universal Function ◽  
Visible Light Communications ◽  
Least Mean Square ◽  
Training Sequences ◽  
Led Nonlinearity ◽  
Electrical Source

By modulating the optical power of the light-emitting diode (LED) in accordance with the electrical source and using a photodetector to convert the corresponding optical variation back into electrical signals, visible light communication (VLC) has been developed to achieve lighting and communications simultaneously, and is now considered one of the promising technologies for handling the continuing increases in data demands, especially indoors, for next generation wireless broadband systems. During the process of electrical-to-optical conversion using LEDs in VLC, however, signal distortion occurs due to LED nonlinearity, resulting in VLC system performance degradation. Artificial neural networks (ANNs) are thought to be capable of achieving universal function approximation, which was the motivation for introducing ANN predistortion to compensate for LED nonlinearity in this paper. Without using additional training sequences, the related parameters in the proposed ANN predistorter can be adaptively updated, using a feedback replica of the original electrical source, to track the LED time-variant characteristics due to temperature variation and aging. Computer simulations and experimental implementation were carried out to evaluate and validate the performance of the proposed ANN predistorter against existing adaptive predistorter schemes, such as the normalized least mean square predistorter and the Chebyshev polynomial predistorter.

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