NIAISPDec 19, 2024

Overview of AI and Communication for 6G Network: Fundamentals, Challenges, and Future Research Opportunities

arXiv:2412.14538v4171 citationsh-index: 116Sci China Inf Sci
Originality Synthesis-oriented
AI Analysis

This is an incremental review paper that synthesizes existing knowledge for researchers and practitioners in telecommunications and AI, outlining a vision for AI-6G integration but not introducing new methods or data.

This paper provides a comprehensive overview of integrating artificial intelligence (AI) with sixth-generation (6G) communication networks to address growing connectivity demands, focusing on foundational principles, challenges, and future research opportunities without presenting specific experimental results or numerical improvements.

With the growing demand for seamless connectivity and intelligent communication, the integration of artificial intelligence (AI) and sixth-generation (6G) communication networks has emerged as a transformative paradigm. By embedding AI capabilities across various network layers, this integration enables optimized resource allocation, improved efficiency, and enhanced system robust performance, particularly in intricate and dynamic environments. This paper presents a comprehensive overview of AI and communication for 6G networks, with a focus on emphasizing their foundational principles, inherent challenges, and future research opportunities. We first review the integration of AI and communications in the context of 6G, exploring the driving factors behind incorporating AI into wireless communications, as well as the vision for the convergence of AI and 6G. The discourse then transitions to a detailed exposition of the envisioned integration of AI within 6G networks, delineated across three progressive developmental stages. The first stage, AI for Network, focuses on employing AI to augment network performance, optimize efficiency, and enhance user service experiences. The second stage, Network for AI, highlights the role of the network in facilitating and buttressing AI operations and presents key enabling technologies, such as digital twins for AI and semantic communication. In the final stage, AI as a Service, it is anticipated that future 6G networks will innately provide AI functions as services, supporting application scenarios like immersive communication and intelligent industrial robots. In addition, we conduct an in-depth analysis of the critical challenges faced by the integration of AI and communications in 6G. Finally, we outline promising future research opportunities that are expected to drive the development and refinement of AI and 6G communications.

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