The success of Artificial Intelligence (AI) in multiple disciplines and vertical domains in recent years has promoted the evolution of mobile networking and the future Internet toward an AI-integrated Internet-of-Things (IoT) era. Nevertheless, most AI techniques rely on data generated by physical devices (e.g., mobile devices and network nodes) or specific applications (e.g., fitness trackers and mobile gaming). To bypass this circumvent, Generative AI (GAI), a.k.a. AI-generated content (AIGC), has emerged as a powerful AI paradigm; thanks to its ability to efficiently learn complex data distributions and generate synthetic data to represent the original data in various forms. This impressive feature is projected to transform the management of mobile networking and diversify the current services and applications provided. On this basis, this work presents a concise tutorial on the role of GAIs in mobile and wireless networking. In particular, this survey first provides the fundamentals of GAI and representative GAI models, serving as an essential preliminary to the understanding of the applications of GAI in mobile and wireless networking. Then, this work provides a comprehensive review of state-of-the-art studies and GAI applications in network management, wireless security, semantic communication, and lessons learned from the open literature. Finally, this work summarizes the current research on GAI for mobile and wireless networking by outlining important challenges that need to be resolved to facilitate the development and applicability of GAI in this edge-cutting area.

翻译：近年来，人工智能在多个学科与垂直领域的成功推动了移动网络与未来互联网向人工智能融合的物联网时代演进。然而，大多数人工智能技术依赖于物理设备（如移动设备与网络节点）或特定应用（如健身追踪器与移动游戏）所产生的数据。为突破此限制，生成式人工智能（亦称人工智能生成内容）作为一种强大的人工智能范式应运而生；其能够高效学习复杂数据分布并生成合成数据，以多种形式表征原始数据。这一卓越特性有望变革移动网络的管理模式，并丰富当前提供的服务与应用。基于此，本文针对生成式人工智能在移动与无线网络中的作用进行了简明导论。具体而言，本综述首先阐释了生成式人工智能的基础原理与代表性模型，为理解其在移动与无线网络中的应用奠定必要基础。随后，系统梳理了网络管理、无线安全、语义通信等领域的前沿研究与生成式人工智能应用案例，并总结了公开文献中的经验启示。最后，通过厘清该前沿领域亟待解决的关键挑战，本文对当前生成式人工智能在移动与无线网络中的研究进行了总结，以促进其在该尖端领域的深入发展与实际应用。