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：传统网络层的核心功能是通过中间网络节点将数据包副本从源节点传输至目标节点。本文提出一种在中间或边缘网络节点部署生成式人工智能（GenAI）的生成式网络层，并分析其对网络所需数据速率的影响。我们通过案例研究验证，GenAI辅助节点可根据高度压缩的潜在表征提示生成图像。基于图像质量约束下的网络流分析结果表明，生成式网络层在所需数据速率方面可实现超过100%的性能提升。