Performance of Deep Learning Assisted Visible Light Communications Impaired by Blockages

This study investigates the performance of visible light communications (VLCs) in the presence of blockages. An indoor office scenario with a single VLC access point serving the user nodes in the presence of human blockages is examined. System performance is assessed through closed-form expressions...

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Bibliographic Details
Main Authors: Shaik, Parvez, Kececi, Cihat, Garg, Kamal K., Boyaci, Ali, Ismail, Muhammad, Serpedin, Erchin
Format: Conference Proceeding
Language:English
Subjects:
Blockage
BPSK
Deep Learning
Probability
QAM
Quadrature amplitude modulation
Receivers
Signal detection
Symbols
System performance
Visible light communication
VLC
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Description
Summary:This study investigates the performance of visible light communications (VLCs) in the presence of blockages. An indoor office scenario with a single VLC access point serving the user nodes in the presence of human blockages is examined. System performance is assessed through closed-form expressions for outage probability and symbol error rate for binary phase shift keying and quadrature amplitude modulation. A deep neural network for symbol detection is deployed at the receiver. Performance metrics illustrate that the blockages cause significant impact on signal detection. Computer simulations corroborate the correctness of the obtained analytical expressions.
ISSN:2576-6813
DOI:10.1109/GLOBECOM54140.2023.10436826