We propose deep learning based communication methods for adaptive-bandwidth
transmission of images over wireless channels. We consider the scenario in which images …

Almost all wireless communication sys-tems today are designed based on essentially the
same digital approach, that separately optimizes the compression and channel coding …

We introduce deep learning based communication methods for successive refinement of
images over wireless channels. We present three different strategies for progressive image …

Semantic communications have shown promising advancements by optimizing source and
channel coding jointly. However, the dynamics of these systems remain understudied …

This letter proposes a semantic importance-aware communication (SIAC) scheme using pre-
trained language models (eg, ChatGPT, BERT, etc.). Specifically, we propose a cross-layer …

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 …

Deep learning (DL) based semantic communication methods have been explored to
transmit images efficiently in recent years. In this paper, we propose a generative model …

We consider wireless transmission of images in the presence of channel output feedback.
From a Shannon theoretic perspective feedback does not improve the asymptotic end-to …

This paper proposes a new wireless video communication scheme to achieve high-
efficiency video transmission over noisy channels. It exploits the idea of model division …

Multi-task learning (MTL) is an efficient way to improve the performance of related tasks by
sharing knowledge. However, most existing MTL networks run on a single end and are not …