The traditional role of the network layer is the transfer of packet replicas from source to destination through intermediate network nodes. We present a generative network layer that uses Generative AI (GenAI) at intermediate or edge network nodes and analyze its impact on the required data rates in the network. We conduct a case study where the GenAI-aided nodes generate images from prompts that consist of substantially compressed latent representations. The results from network flow analyses under image quality constraints show that the generative network layer can achieve an improvement of more than 100% in terms of the required data rate.

翻译：传统网络层的功能是通过中间网络节点将数据包副本从源端传输至目的端。本文提出一种在中间或边缘网络节点上应用生成式人工智能（GenAI）的生成式网络层，并分析其对网络所需数据传输速率的影响。我们通过案例研究，使GenAI辅助节点根据包含高度压缩潜在表征的提示词生成图像。在图像质量约束条件下的网络流分析结果表明，该生成式网络层在所需数据传输速率方面可实现超过100%的提升。