@inproceedings{f25f7dae274840458d70551ba29fa28d,
title = "Performance of Deep Learning Assisted Visible Light Communications Impaired by Blockages",
abstract = "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.",
keywords = "BPSK, Blockage, Deep Learning, QAM, VLC",
author = "Parvez Shaik and Cihat Ke{\c c}eci and Garg, {Kamal K.} and Ali Boyaci and Muhammad Ismail and Erchin Serpedin",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE Global Communications Conference, GLOBECOM 2023 ; Conference date: 04-12-2023 Through 08-12-2023",
year = "2023",
doi = "10.1109/GLOBECOM54140.2023.10436826",
language = "English",
series = "Proceedings - IEEE Global Communications Conference, GLOBECOM",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4704--4709",
booktitle = "GLOBECOM 2023 - 2023 IEEE Global Communications Conference",
}