Rate-Adaptive Coding Mechanism for Semantic Communications With Multi-Modal Data

Understand

Recently, the ever-increasing demand for bandwidth in multi-modal communication systems requires a paradigm shift.

• Powered by deep learning, semantic communications are applied to multi-modal scenarios to boost communication efficiency and save communication resources.
• However, the existing end-to-end neural network (NN) based framework without the channel encoder/decoder is incompatible with modern digital communication systems.
• Moreover, most end-to-end designs are task-specific and require re-design and re-training for new tasks, which limits their applications.