AI–6G Convergence: Architectures, Key Use Cases, and Challenges for Intelligent and Sustainable Networks
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Updated time：2025-12-23 13:12:21 Views：91
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Abstract
The sixth generation (6G) of wireless communication systems is poised to transcend the performance-oriented objectives of 5G, evolving into an intelligent, adaptive, and context-aware network paradigm. Central to this transformation is the deep integration of Artificial Intelligence (AI) across all layers of the communication stack, enabling AI-native architectures that deliver self-optimization, self-healing, semantic understanding, and autonomous decision-making. This paper presents a comprehensive examination of the AI–6G convergence, beginning with an overview of AI-native design principles and the transition from AI-assisted to AI-intrinsic networks. Key use cases are explored, including intelligent extended reality, AI-driven digital twins, autonomous mobility, AI-augmented remote healthcare, joint communication and sensing, sustainable smart cities, intelligent network management, and industrial automation. We analyze the enabling technologies—such as edge AI computing, federated learning, reconfigurable intelligent surfaces, and terahertz communication systems—that are required to realize this vision. Furthermore, we discuss the core technical, ethical, and operational challenges that must be addressed to ensure that AI–6G systems are scalable, secure, explainable, and sustainable. The insights presented aim to guide researchers, industry practitioners, and policymakers in shaping a trustworthy and inclusive 6G ecosystem that aligns with global sustainability goals. This research focuses on applications such as sustainable smart cities, autonomous mobility, and augmented healthcare, directly advancing SDG-9 (Industry, Innovation, and Infrastructure) by building resilient and innovative infrastructure. Its overarching goals of sustainability and inclusiveness also support SDG-11 (Sustainable Cities and Communities).
Keywords
6G networks, Artificial Intelligence, AI-native architecture, intelligent connectivity, semantic communication, digital twins, edge AI, joint communication and sensing, reconfigurable intelligent surfaces, terahertz communications, sustainable smart citie
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