  Mobile multimedia networks (MMNs) demonstrate great potential in delivering
low-latency and high-quality entertainment and tactical applications, such as
short-video sharing, online conferencing, and battlefield surveillance. For
instance, in tactical surveillance of battlefields, scalability and
sustainability are indispensable for maintaining large-scale military
multimedia applications in MMNs. Therefore, many data-driven networking
solutions are leveraged to optimize streaming strategies based on real-time
traffic analysis and resource monitoring. In addition, generative AI (GAI) can
not only increase the efficiency of existing data-driven solutions through data
augmentation but also develop potential capabilities for MMNs, including
AI-generated content (AIGC) and AI-aided perception. In this article, we
propose the framework of GAI-enabled MMNs that leverage the capabilities of GAI
in data and content synthesis to distribute high-quality and immersive
interactive content in wireless networks. Specifically, we outline the
framework of GAI-enabled MMNs and then introduce its three main features,
including distribution, generation, and perception. Furthermore, we propose a
second-score auction mechanism for allocating network resources by considering
GAI model values and other metrics jointly. The experimental results show that
the proposed auction mechanism can effectively increase social welfare by
allocating resources and models with the highest user satisfaction.
