Recently, the ever-increasing demand for bandwidth in multi-modal communication systems
requires a paradigm shift. Powered by deep learning, semantic communications are applied …

Task-oriented semantic communications have achieved significant performance gains.
However, the employed deep neural networks in semantic communications have to be …

In 6G communication, semantic communication is considered one of the most promising
directions to fulfill users' demands for immersive multi-modal experiences, low latency, and …

Traditional adaptive modulation scheme aims to maximize the spectral efficiency by
selecting the appropriate modulation scheme under the premise of perfect bit-level data …

Semantic communications have emerged as a new paradigm for improving communication
efficiency by transmitting the semantic information of a source message that is most relevant …

Traditional rate adaptive mechanism aims to maximize spectral efficiency by choosing the
optimal transmission under the premise of perfect bit-level data transmission. However, in …

It is well known that multi-modal services, including video, audio, and haptic signals, aim to
provide immersive experience with low latency and high reliability. Although multi-modal …

Semantic communication has emerged as a promising approach for improving efficient
transmission in the next generation of wireless networks. Inspired by the success of …

Recent deep learning methods have led to increased interest in solving high-efficiency end-
to-end transmission problems. These methods, we call nonlinear transform source-channel …

Multimodal signals, including text, audio, image and video, can be integrated into Semantic
Communication (SC) for providing an immersive experience with low latency and high …