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

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 …

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

In this paper, we propose a novel joint source-channel coding (JSCC) approach for channel-
adaptive digital semantic communications. In semantic communication systems with digital …

In learning-based semantic communications, neural networks have replaced different
building blocks in traditional communication systems. However, the digital modulation still …

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 …

Standard digital communication techniques allow us to set aside the meaning of the
messages to concentrate on the transmission of bits efficiently and reliably. However, with …

The burgeoning generative artificial intelligence technology offers novel insights into the
development of semantic communication (SemCom) frameworks. These frameworks hold …

Although the semantic communications have exhibited satisfactory performance in a large
number of tasks, the impact of semantic noise and the robustness of the systems have not …

Semantic communications target to reliably convey the semantic meaning of messages. It is
different from existing communication systems focusing on reliable bit transmission. To …