Over-the-air Wireless Federated Learning Model for Generative AI

Abstract

<p>Generative artificial intelligence (GenAI) technologies represent an important advancement in the field of AI, particularly for their capabilities in text and image generation. Over-the-air wireless federated learning (OA-WFL) can utilize the wireless waveform superposition property to achieve efficient model aggregation, thereby providing support for GenAI training and deployment. Therefore, this article investigates the support of OA-WFL for GenAI, focusing on potential applications and specific examples. We first discuss the OA-WFL and GenAI models, emphasizing their functionalities and the potential benefits arising from their interaction. We then explore its application in various GenAI scenarios, including large-scale edge device content generation, efficient distributed training of GenAI models, and reduction of bandwidth requirements and device load. Next, a framework is proposed to apply OA-WFL to diffusion models, such as those used in image generation, and validate its effectiveness through simulation results. Finally, we discuss prospective research directions for the application of OA-WFL for GenAI.</p>