2025/06/29 by João Loureiro, Loureiro, João Pedro, Delgado, Patrícia +5
Computer Science · Earth and Planetary Sciences · Engineering · #FOS: Computer and information sciences #Networking and Internet Architecture (cs.NI) #Underwater Acoustics Research #Underwater Vehicles and Communication Systems #Wireless Signal Modulation Classification
paper · pdf · doi:10.48550/arxiv.2506.23350
openalex publication_date 2025/06/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30
Underwater wireless communications face significant challenges due to propagation constraints, limiting the effectiveness of traditional radio and optical technologies. Long-range acoustic communications support distances up to a few kilometers, but suffer from low bandwidth, high error ratios, and multipath interference. Semantic communications, which focus on transmitting extracted semantic features rather than raw data, present a promising solution by significantly reducing the volume of data transmitted over the wireless link. This paper evaluates the resilience of SAGE, a semantic-oriented communications framework that combines semantic processing with Generative Artificial Intelligence (GenAI) to compress and transmit image data as textual descriptions over acoustic links. To assess robustness, we use a custom-tailored simulator that introduces character errors observed in underwater acoustic channels. Evaluation results show that SAGE can successfully reconstruct meaningful image content even under varying error conditions, highlighting its potential for robust and efficient underwater wireless communication in harsh environments.