Generative Semantic Communication

Generative semantic communication aims to improve communication efficiency by transmitting only the essential semantic meaning of data, rather than the raw data itself, leveraging generative AI models for reconstruction at the receiver. Current research focuses on applying diffusion models, transformers, and vector quantization techniques to achieve this, often within frameworks incorporating personalized federated learning for multi-user scenarios and addressing challenges like latency and channel noise. This approach holds significant promise for enhancing the efficiency and robustness of communication systems across various applications, including image and speech transmission, particularly in bandwidth-constrained or resource-limited environments.