A Semantic-oriented Approach for Underwater Wireless Communications using Generative AI

Underwater wireless communications are crucial for supporting multiple maritime activities, such as environmental monitoring and offshore wind farms. However, the challenging underwater environment continues to pose obstacles to the development of long-range, broadband underwater wireless communication systems. State of the art solutions are limited to long range, narrowband acoustics and short range, broadband radio or optical communications. This precludes real-time wireless transmission of imagery over long distancesIn this paper, we propose SAGE, a semantic-oriented underwater communications approach to enable real-time wireless imagery transmission over noisy and narrowband channels. SAGE extracts semantically relevant information from images at the sender located underwater and generates a text description that is transmitted to the receiver at the surface, which in turn generates an image from the received text description. SAGE is evaluated using BLIP for image-to-text and Stable Diffusion for text-to-image, showing promising image similarity between the original and the generated images, and a significant reduction in latency up to a hundred-fold, encouraging further research in this area.