arXiv:2604.02370cs.NIcs.AI2026-04综述被引 7

AI驱动6G网络变革,提升连接能力与智能水平

A Survey on AI for 6G: Challenges and Opportunities

  • 融合深度学习、强化学习等AI技术构建智能6G网络
  • 支持URLLC、eMBB等场景,实现低延迟高可靠通信
  • 适合关注6G与AI交叉研究的学者及工程师

随着无线通信的发展,每一代网络都引入新技术,改变人们的连接方式。人工智能(AI)正成为塑造第六代(6G)网络未来的关键。通过结合人工智能与机器学习(ML),6G旨在为智慧城市、自动驾驶、全息远程呈现和触觉互联网等应用提供高速率、低延迟和广泛连接。本文详细概述了AI在支持6G网络中的作用,重点介绍深度学习、强化学习、联邦学习和可解释AI等关键技术。同时探讨了AI与核心网络功能的集成,分析了可扩展性、安全性和能效等方面的挑战及新解决方案。此外,本文将AI驱动的分析与6G服务领域如超可靠低延迟通信(URLLC)、增强移动宽带(eMBB)、大规模机器类通信(mMTC)和感知与通信一体化(ISAC)相联系。还讨论了标准化、伦理和可持续性等问题。通过总结近期研究趋势并指明未来方向,本综述为人工智能与下一代无线通信交叉领域的研究人员和从业者提供了宝贵参考。

原文摘要 · Abstract (English)

As wireless communication evolves, each generation of networks brings new technologies that change how we connect and interact. Artificial Intelligence (AI) is becoming crucial in shaping the future of sixth-generation (6G) networks. By combining AI and Machine Learning (ML), 6G aims to offer high data rates, low latency, and extensive connectivity for applications including smart cities, autonomous systems, holographic telepresence, and the tactile internet. This paper provides a detailed overview of the role of AI in supporting 6G networks. It focuses on key technologies like deep learning, reinforcement learning, federated learning, and explainable AI. It also looks at how AI integrates with essential network functions and discusses challenges related to scalability, security, and energy efficiency, along with new solutions. Additionally, this work highlights perspectives that connect AI-driven analytics to 6G service domains like Ultra-Reliable Low-Latency Communication (URLLC), Enhanced Mobile Broadband (eMBB), Massive Machine-Type Communication (mMTC), and Integrated Sensing and Communication (ISAC). It addresses concerns about standardization, ethics, and sustainability. By summarizing recent research trends and identifying future directions, this survey offers a valuable reference for researchers and practitioners at the intersection of AI and next-generation wireless communication.

6G人工智能网络智能通信

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