Enhancing UAV Network Efficiency through 6G<sup>+</sup> Enabled Federated Learning Algorithms and Energy optimization Techniques-Reference-Cited by-同舟云学术

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Enhancing UAV Network Efficiency through 6G⁺ Enabled Federated Learning Algorithms and Energy optimization Techniques

Published:2024-05-27 Issue: Volume: Page:192-197
ISSN:
Container-title:2024 International Wireless Communications and Mobile Computing (IWCMC)
language:
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Author:

Andreou Andreas¹,Mavromoustakis Constandinos X.¹,Batalla Jordi Mongay²,Markakis Evangelos²,Bourdena Athina³,Mastorakis George⁴,Song Houbing⁵

Affiliation:

1. University of Nicosia,Department of Computer Science,Nicosia,Cyprus

2. Warsaw University of Technology,Warsaw,Poland

3. Hellenic Mediterranean University,Department of Electrical and Computer Engineering,Heraklion,Crete,Greece

4. Hellenic Mediterranean University,Department of Management Science and Technology,Agios Nikolaos,Crete,Greece

5. University of Maryland,Department of Information Systems,Baltimore,MD,USA,21250

Funder

Research and Development

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10592105/10592309/10592391.pdf?arnumber=10592391

Reference16 articles.

1. UAV-Assisted RSUs for V2X Connectivity Using Voronoi Diagrams in 6G⁺ Infrastructures

2. A Novel 3D UAV Channel Model for A2G Communication Environments Using AoD and AoA Estimation Algorithms

3. UAV Trajectory Optimisation in Smart Cities Using Modified A^* Algorithm Combined With Haversine and Vincenty Formulas

4. Applied AI in instrumentation and measurement: The deep learning revolution

5. Adaptive Granularity Learning Distributed Particle Swarm Optimization for Large-Scale Optimization

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