Federated Learning Techniques for 5G Mobile Networks-Reference-Cited by-同舟云学术

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Federated Learning Techniques for 5G Mobile Networks

Published:2022-02-22 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 16th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET)
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Author:

Shubyn Bohdan¹,Mrozek Dariusz²,Fabry Ludvig³,Maksymyuk Taras¹,Amhoud El Mehdi⁴,Gazda Juraj⁵

Affiliation:

1. Lviv Polytechnic National University, Silesian University of Technology,Lviv,Ukraine

2. Silesian University of Technology,Department of Applied Informatics,Gliwice,Poland

3. Lviv Polytechnic National University,Lviv,Ukraine

4. Mohammed VI Polytechnic University,Ben Guerir,Morocco

5. Technical University of Kosice,Kosice,Slovakia

Funder

Slovak Research and Development Agency

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9766439/9766835/09767080.pdf?arnumber=9767080

Reference15 articles.

1. Radio Resource Management Methods for Ultra-Reliable Low-Latency Communications in 5G LTE Narrowband Industrial Internet of Things

2. Intelligent Spectrum Management in 5G Mobile Networks based on Recurrent Neural Networks

3. A Modified Genetic Algorithm for Increasing the Efficiency of Routing in Self-Organized Networks

4. Intelligent Handover Management in 5G Mobile Networks based on Recurrent Neural Networks

5. Reliable Federated Learning for Mobile Networks

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