Semantic Transmission

Semantic transmission aims to efficiently convey the meaning of information, rather than focusing solely on accurate bit-by-bit reproduction, leveraging the inherent redundancy and predictability of data. Current research emphasizes the use of deep learning models, particularly transformers and diffusion models, often integrated with reinforcement learning algorithms, to extract and transmit semantic features across various data types (text, speech, images, video). This approach promises significant improvements in bandwidth efficiency and robustness for applications like the Internet of Vehicles and 6G networks, impacting both communication systems and AI-driven tasks.