Performance of Deep Learning Assisted Visible Light Communications Impaired by Blockages

Parvez Shaik; Cihat Keçeci; Kamal K. Garg; Ali Boyaci; Muhammad Ismail; Erchin Serpedin

doi:10.1109/GLOBECOM54140.2023.10436826

Performance of Deep Learning Assisted Visible Light Communications Impaired by Blockages

Parvez Shaik
, Cihat Keçeci
, Kamal K. Garg
, Ali Boyaci
, Muhammad Ismail
, Erchin Serpedin

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	GLOBECOM 2023 - 2023 IEEE Global Communications Conference
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4704-4709
Number of pages	6
ISBN (Electronic)	9798350310900
DOIs	https://doi.org/10.1109/GLOBECOM54140.2023.10436826
State	Published - 2023
Externally published	Yes
Event	2023 IEEE Global Communications Conference, GLOBECOM 2023 - Kuala Lumpur, Malaysia Duration: Dec 4 2023 → Dec 8 2023

Publication series

Name	Proceedings - IEEE Global Communications Conference, GLOBECOM
ISSN (Print)	2334-0983
ISSN (Electronic)	2576-6813

Conference

Conference	2023 IEEE Global Communications Conference, GLOBECOM 2023
Country/Territory	Malaysia
City	Kuala Lumpur
Period	12/4/23 → 12/8/23

Funding

b1−a1a1 IS2c=B12Γ(a1)b1 Γ(a1,b1γmax). ACKNOWLEDGMENT This publication was made possible by NPRP grant #NPRP13S-0127-200182 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. REFERENCES

Keywords

BPSK
Blockage
Deep Learning
QAM
VLC

Access to Document

10.1109/GLOBECOM54140.2023.10436826

Cite this

Shaik, P., Keçeci, C., Garg, K. K., Boyaci, A., Ismail, M., & Serpedin, E. (2023). Performance of Deep Learning Assisted Visible Light Communications Impaired by Blockages. In GLOBECOM 2023 - 2023 IEEE Global Communications Conference (pp. 4704-4709). (Proceedings - IEEE Global Communications Conference, GLOBECOM). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GLOBECOM54140.2023.10436826

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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.",

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}

Shaik, P, Keçeci, C, Garg, KK, Boyaci, A, Ismail, M & Serpedin, E 2023, Performance of Deep Learning Assisted Visible Light Communications Impaired by Blockages. in GLOBECOM 2023 - 2023 IEEE Global Communications Conference. Proceedings - IEEE Global Communications Conference, GLOBECOM, Institute of Electrical and Electronics Engineers Inc., pp. 4704-4709, 2023 IEEE Global Communications Conference, GLOBECOM 2023, Kuala Lumpur, Malaysia, 12/4/23. https://doi.org/10.1109/GLOBECOM54140.2023.10436826

Performance of Deep Learning Assisted Visible Light Communications Impaired by Blockages. / Shaik, Parvez; Keçeci, Cihat; Garg, Kamal K. et al.
GLOBECOM 2023 - 2023 IEEE Global Communications Conference. Institute of Electrical and Electronics Engineers Inc., 2023. p. 4704-4709 (Proceedings - IEEE Global Communications Conference, GLOBECOM).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Ismail, Muhammad

AU - Serpedin, Erchin

PY - 2023

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N2 - 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.

AB - 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.

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KW - Deep Learning

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KW - VLC

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M3 - Conference contribution

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Shaik P, Keçeci C, Garg KK, Boyaci A, Ismail M, Serpedin E. Performance of Deep Learning Assisted Visible Light Communications Impaired by Blockages. In GLOBECOM 2023 - 2023 IEEE Global Communications Conference. Institute of Electrical and Electronics Engineers Inc. 2023. p. 4704-4709. (Proceedings - IEEE Global Communications Conference, GLOBECOM). doi: 10.1109/GLOBECOM54140.2023.10436826

Performance of Deep Learning Assisted Visible Light Communications Impaired by Blockages

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