We present a novel adaptive deep joint source-channel coding (JSCC) scheme for wireless
image transmission. The proposed scheme supports multiple rates using a single deep …

Semantic communications are expected to accomplish various semantic tasks with relatively
less spectrum resource by exploiting the semantic feature of source data. To simultaneously …

As one of the key techniques to realize semantic communications, end-to-end optimized
neural joint source-channel coding (JSCC) has made great progress over the past few …

In this paper, we propose a class of high-efficiency deep joint source-channel coding
methods that can closely adapt to the source distribution under the nonlinear transform, it …

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

Recently, semantic communication has been investigated to boost the performance of end-
to-end image transmission systems. However, existing semantic approaches are generally …

Diffusion models (DM) can gradually learn to remove noise, which have been widely used in
artificial intelligence generated content (AIGC) in recent years. The property of DM for …

Semantic-oriented communication has been considered a promising method to boost
bandwidth efficiency by only transmitting the semantics of the data. In this paper, we propose …

The emerging field semantic communication is driving the research of end-to-end data
transmission. By utilizing the powerful representation ability of deep learning models …

Recent progress in deep learning (DL)-based joint source-channel coding (DeepJSCC) has
led to a new paradigm of semantic communications. Two salient features of DeepJSCC …