Pireci Sejdiu, Nora and Rendevski, Nikola and Ristevski, Blagoj (2024) AI Revolutionizing 5G and Next-Generation Networks. In: 2024 IEEE 17th International Scientific Conference on Informatics (Informatics 2024), 13-15 November 2024, Poprad, Slovakia.
Full text not available from this repository.Abstract
The introduction of 5G and beyond (B5G) networks has transformed massively telecommunications resulting in enhanced capacity, speed, and connectivity of mobile communications. The requirements and the complexity of these networks need to be addressed by innovative approaches to effective network management and optimization. This paper analyzes the critical role of Artificial Intelligence (AI) and Machine Learning (ML) in upgrading next-generation mobile networks and provides a comprehensive analysis of how AI and ML are integrated into 5G systems, highlighting the ways these technologies improve security, edge computing, and network management. It also details the evolution of AI, from the onset in symbolic logic to modern neural networks, and its application in network optimization, including computational offloading, beamforming design, and resource management. AI-driven Self-Organizing Networks (SON) provide adaptive network management and predictive maintenance, while AI-powered edge computing deals with the real-time processing demands of applications such as autonomous vehicles and smart cities. Moreover, the paper also explores how AI improves network security by enhancing threat detection and response capabilities. It concludes by highlighting key future directions, including the integration of AI with emerging technologies such as blockchain and advancements in edge computing. The AI and 5G fusion offer a new era of connected intelligence, revolutionizing the way we interact with technology and one another. This convergence is about transforming communication and connectivity, laying the foundations for more innovative applications and more resilient network infrastructure.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Scientific Fields (Frascati) > Natural sciences > Computer and information sciences Scientific Fields (Frascati) > Engineering and Technology > Electrical engineering, electronic engineering,information engineering |
| Divisions: | Faculty of Information and Communication Technologies |
| Depositing User: | Prof. d-r. Blagoj Ristevski |
| Date Deposited: | 19 Nov 2025 08:58 |
| Last Modified: | 19 Nov 2025 08:58 |
| URI: | https://eprints.uklo.edu.mk/id/eprint/11214 |
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