In this paper, we introduce a novel semantic generative communication (SGC) framework, where generative users leverage text-to-image (T2I) generators to create images locally from downloaded text prompts, while non-generative users directly download images from a base station (BS). Although generative users help reduce downlink transmission energy at the BS, they consume additional energy for image generation and for uploading their generator state information (GSI). We formulate the problem of minimizing the total energy consumption of the BS and the users, and devise a generative user selection algorithm. Simulation results corroborate that our proposed algorithm reduces total energy by up to 54% compared to a baseline with all non-generative users.

翻译：本文提出了一种新颖的语义生成通信（SGC）框架，其中生成型用户利用文本到图像（T2I）生成器根据下载的文本提示在本地生成图像，而非生成型用户则直接从基站（BS）下载图像。尽管生成型用户有助于降低基站在下行传输中的能耗，但它们会在图像生成和上传生成器状态信息（GSI）的过程中消耗额外能量。本文构建了最小化基站与用户总能耗的优化问题，并设计了一种生成型用户选择算法。仿真结果证实，与所有用户均为非生成型的基准方案相比，所提算法可将总能耗降低高达54%。