Generative Network Layer for Communication Systems with Artificial Intelligence

被引：0
|
作者：
Thorsager, Mathias [1 ]
Leyva-Mayorga, Israel [1 ]
Soret, Beatriz [1 ,2 ]
Popovski, Petar [1 ]
机构：
[1] Aalborg University, Department of Electronic Systems, Aalborg,9220, Denmark
[2] Telecommunications Research Institute, University of Malaga, Malaga,29071, Spain
来源：
IEEE Networking Letters | 2024年 / 6卷 / 02期
关键词：
Communications systems - Data-rate - Distortion measurement - Generative AI - Intermediate networks - Network node - Network topology - Networking - Networks flows - Prompting;
D O I：
10.1109/LNET.2024.3354114
中图分类号：
学科分类号：
摘要：
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. © 2019 IEEE.
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页码：82 / 86
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