From Theory to Practice: Implementing Meta-Learning in 6G Wireless Infrastructure

The vision of the sixth generation of communication systems, commonly known as 6G, entails a connected world that provides ubiquitous connectivity and fosters the digital transformation of society. As the number of devices, services, and users continues to grow, intelligent solutions are expected to facilitate this transformation. This paper considers meta-learning as a pivotal paradigm for 6G systems, detailing its principles, algorithms, and theoretical underpinnings. The methodology involves integrating meta-learning with three potential 6G technologies: RF-based communication systems, optical communication systems, and molecular communication systems. The findings reveal the distinct characteristics of these technologies and demonstrate the potential benefits and challenges of incorporating meta-learning algorithms. Practical implications highlight how meta-learning can enhance the efficiency and adaptability of 6G systems, addressing the growing demand for intelligent and seamless communication networks.

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Publication Details

Journal
Telecom
Published
2024-12-06
DOI
https://doi.org/10.3390/telecom5040063
Primary Topic
Wireless Signal Modulation Classification
Type
article
Field-Weighted Citation Impact
0.00
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article

From Theory to Practice: Implementing Meta-Learning in 6G Wireless Infrastructure

Messaoud Ahmed Ouameur, Arooba Zeshan, Tuan-Anh D. Le, Muhammad Zeshan Alam
Telecom
Wireless Signal Modulation Classification
article

From Theory to Practice: Implementing Meta-Learning in 6G Wireless Infrastructure

Messaoud Ahmed Ouameur, Arooba Zeshan, Tuan-Anh D. Le, Muhammad Zeshan Alam
article en

Abstract

The vision of the sixth generation of communication systems, commonly known as 6G, entails a connected world that provides ubiquitous connectivity and fosters the digital transformation of society. As the number of devices, services, and users continues to grow, intelligent solutions are expected to facilitate this transformation. This paper considers meta-learning as a pivotal paradigm for 6G systems, detailing its principles, algorithms, and theoretical underpinnings. The methodology involves integrating meta-learning with three potential 6G technologies: RF-based communication systems, optical communication systems, and molecular communication systems. The findings reveal the distinct characteristics of these technologies and demonstrate the potential benefits and challenges of incorporating meta-learning algorithms. Practical implications highlight how meta-learning can enhance the efficiency and adaptability of 6G systems, addressing the growing demand for intelligent and seamless communication networks.

TelecomVol. 5(4)
Ho Chi Minh City University of Science (VN), Brandon University (CA), Université du Québec à Trois-Rivières (CA), The University of Winnipeg (CA)
Industry, innovation and infrastructure
Openalex Percentile: Top 80%
Wireless Signal Modulation Classification
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