Deep Learning Based Proactive Optimization for Mobile LiFi Systems With Channel Aging-Reference-Cited by-同舟云学术

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Deep Learning Based Proactive Optimization for Mobile LiFi Systems With Channel Aging

Published:2024-06 Issue:6 Volume:72 Page:3543-3557
ISSN:0090-6778
Container-title:IEEE Transactions on Communications
language:
Short-container-title:IEEE Trans. Commun.

Author:

Arfaoui Mohamed Amine¹^ORCID,Ghrayeb Ali²^ORCID,Assi Chadi³^ORCID,Qaraqe Marwa⁴^ORCID

Affiliation:

1. InterDigital Canada Ltee, Montreal, QC, Canada

2. Electrical and Computer Engineering (ECE) Department, Texas A&M University at Qatar, Doha, Qatar

3. Concordia Institute for Information Systems Engineering (CIISE), Concordia University, Montreal, QC, Canada

4. College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar

Funder

Qatar National Research Fund

Concordia University

les Fonds de Recherche du Québec-Nature et Technologies

Natural Sciences and Engineering Research Council of Canada

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/26/10559904/10436649.pdf?arnumber=10436649

Reference56 articles.

1. A Vision of 6G Wireless Systems: Applications, Trends, Technologies, and Open Research Problems

2. 6G Wireless Networks: Vision, Requirements, Architecture, and Key Technologies

3. What is LiFi?

4. 6G Vision and Requirements: Is There Any Need for Beyond 5G?

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