This paper describes a methodology for evaluating the operational rate-distortion behavior
of combined source and channel coding schemes with particular application to images. In …

Recently, learning-based image compression model has attracted much attention due to its
impressive performance and ease of optimization, compared with traditional DCT and …

We consider the problem of joint source and channel coding of structured data such as
natural language over a noisy channel. The typical approach to this problem in both theory …

We study the collaborative image retrieval problem at the wireless edge, where multiple
edge devices capture images of the same object from different angles and locations, which …

We consider the wireless text transmission using joint source-channel coding (JSCC).
Classical source coding only considers the syntactic information based on probabilistic …

Optimizing precoding with deep learning enables its real-time implementation. In addition to
the learning perfor-mance such as sum rate, training complexity is also important since …

This paper presents a vision transformer (ViT) based joint source and channel coding
(JSCC) scheme for wireless image transmission over multiple-input multiple-output (MIMO) …

A wireless video communication system can be designed based on the rate-distortion (RD)
criterion, ie, minimizing the end-to-end distortion (which includes quantization distortion and …

Over recent years, deep learning-based computer vision systems have been applied to
images at an ever-increasing pace, oftentimes representing the only type of consumption for …

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 …