With the phenomenal success of diffusion models and ChatGPT, deep generation
models (DGMs) have been experiencing explosive growth from 2022. Not limited to
content generation, DGMs are also widely adopted in Internet of Things,
Metaverse, and digital twin, due to their outstanding ability to represent
complex patterns and generate plausible samples. In this article, we explore
the applications of DGMs in a crucial task, i.e., improving the efficiency of
wireless network management. Specifically, we firstly overview the generative
AI, as well as three representative DGMs. Then, a DGM-empowered framework for
wireless network management is proposed, in which we elaborate the issues of
the conventional network management approaches, why DGMs can address them
efficiently, and the step-by-step workflow for applying DGMs in managing
wireless networks. Moreover, we conduct a case study on network economics,
using the state-of-the-art DGM model, i.e., diffusion model, to generate
effective contracts for incentivizing the mobile AI-Generated Content (AIGC)
services. Last but not least, we discuss important open directions for the
further research.

本文讨论深度生成模型在无线网络管理中的应用，探讨了传统网络管理方法的问题，提出了一种 DGM 增强的框架，并对网络经济进行了案例研究。