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Artificial Intelligence for 5G and 6G Networks: A Taxonomy-Based Survey of Applications, Trends, and Challenges

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Pubblicato in:Technologies vol. 13, no. 12 (2025), p. 559-609
Autore principale: Nouri, Omheni
Altri autori: Koubaa Hend, Zarai Faouzi
Pubblicazione:
MDPI AG
Soggetti:
Wireless communications
Network function virtualization
Interoperability
Collaboration
Deep learning
Internet of Things
Network security
5G mobile communication
Mobile communications networks
Real time
Taxonomy
Architecture
Ethics
Machine learning
Ethical standards
Federated learning
Explainable artificial intelligence
Virtual reality
Technology
Cognition & reasoning
Data integrity
Artificial intelligence
Trends
6G mobile communication
Networks
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Abstract:The mobile network ecosystem is undergoing profound change driven by Artificial Intelligence (AI), Network Function Virtualization (NFV), and Software-Defined Networking (SDN). These technologies are well positioned to enable the essential transformation of next-generation networks, delivering significant improvements in efficiency, flexibility, and sustainability. AI is expected to impact the entire lifecycle of mobile networks, including design, deployment, service implementation, and long-term management. This article reviews the key characteristics of 5G and the anticipated technology enablers of 6G, focusing on the integration of AI within mobile networks. This study addresses several perspectives, including network optimization, predictive analytics, and security enhancement. A taxonomy is proposed to classify AI applications into 5G and 6G according to their role in network operations and their impact across vertical domains such as the Internet of Things (IoT), healthcare, and transportation. Furthermore, emerging trends are discussed, including federated learning, advanced AI models, and explainable AI, along with major challenges related to data privacy, adaptability, and interoperability. This paper concludes with future research directions, emphasizing the importance of ethical AI policies and cross-sector collaborations to ensure effective and sustainable AI-enabled mobile networks.
ISSN:2227-7080
DOI:10.3390/technologies13120559
Fonte:Materials Science Database