Semantic Communication System

Semantic communication systems aim to transmit the meaning of information rather than raw data, prioritizing efficient conveyance of essential semantic content. Current research focuses on developing deep learning-based transceivers, often employing transformer networks and generative AI models like diffusion models, to achieve robust and efficient communication across various channels and modalities (image, text, speech). This approach shows promise in improving data transmission efficiency, particularly in bandwidth-constrained environments and interference-prone scenarios, with applications ranging from autonomous driving to 6G networks. Furthermore, significant effort is dedicated to developing appropriate evaluation metrics that capture semantic similarity, rather than relying solely on traditional signal-to-noise ratio or distortion measures.