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

The task-oriented semantic communication sys-tems have achieved significant performance
gain, however, the paradigm that employs a model for a specific task might be limited, since …

While semantic communications have shown the potential in the case of single-modal single-
users, its applications to the multi-user scenario remain limited. In this paper, we investigate …

Recently, deep learned enabled end-to-end communication systems have been developed
to merge all physical layer blocks in the traditional communication systems, which make joint …

Semantic communication in the 6G era has been deemed a promising communication
paradigm to break through the bottleneck of traditional communications. However, its …

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 is regarded as the breakthrough beyond the Shannon paradigm,
which transmits the semantic information only to improve the communication efficiency …

Semantic communication has become a widely researched area due to its high spectrum
efficiency and error correction capabilities. Some studies used deep learning to extract …

Existing deep learning-enabled semantic communication systems often rely on shared
background knowledge between the transmitter and receiver that includes empirical data …

Multinode communication, which refers to the interaction among multiple devices, has
attracted lots of attention in many Internet of Things (IoT) scenarios. However, its huge …