Unveiling the future: A comprehensive analysis of 6G technology and its transformative potential

Megha Jain (), Ravi Verma (), Sunil Kumar (), Gyanendra Kumar (), Vinay Chamola () and Mohsen Guizani ()
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Megha Jain: VIT Bhopal University
Ravi Verma: VIT Bhopal University
Sunil Kumar: Manipal University Jaipur
Gyanendra Kumar: Manipal University Jaipur
Vinay Chamola: Birla Institute of Technology and Science
Mohsen Guizani: Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI)

Telecommunication Systems: Modelling, Analysis, Design and Management, 2025, vol. 88, issue 3, No 11, 38 pages

Abstract: Abstract Sixth-generation (6G) technology signifies a major leap in mobile communications, offering ultra-reliable, low-latency, and high-throughput connectivity. This review investigates the foundational technologies underpinning 6G, including Terahertz (THz) communication and ultra-massive multiple input, multiple output (MIMO), and explores their capabilities in enabling high-speed, consistent, and scalable communication infrastructures. A key focus of this study is the application of machine learning (ML) and deep learning (DL) in optimizing network slicing and addressing security challenges within 6G networks. While network slicing allows for flexible, service-specific logical network partitions, it also introduces technical challenges such as dynamic resource allocation, secure slice isolation, and real-time threat detection. To mitigate these, we assess ML-driven approaches—including reinforcement learning (RL), federated learning, and anomaly detection models—that facilitate intelligent orchestration and adaptive security. Furthermore, we highlight practical deployment barriers such as data privacy concerns, computational limitations at the edge, and the need for interpretable models and standardization. This comprehensive review provides insights into the current state, challenges, and potential solutions for integrating ML-based mechanisms to enhance the efficiency, scalability, and security of next-generation communication systems. Graphical abstract

Keywords: 6G Network; Machine Learning Techniques; Deep Learning; Network Slicing; Network Security; Telecommunication Infrastructure (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11235-025-01323-w

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