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

Recent works have shown that the task of wireless transmission of images can be learned
with the use of machine learning techniques. Very promising results in end-to-end image …

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

We consider wireless transmission of images in the presence of channel output feedback, by
introducing an autoencoder-based deep joint source-channel coding (JSCC) scheme. We …

We propose a joint source and channel coding (JSCC) technique for wireless image
transmission that does not rely on explicit codes for either compression or error correction; …

Recent works have shown that modern machine learning techniques can provide an
alternative approach to the long-standing joint source-channel coding (JSCC) problem. Very …

Considering the problem of joint source-channel coding (JSCC) for multi-user transmission
of images over noisy channels, an autoencoder-based novel deep joint source-channel …

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 …

Joint source and channel coding (JSCC) for image transmission has attracted increasing
attention due to its robustness and high efficiency. However, the existing deep JSCC …

Recent works have shown that joint source-channel coding (JSCC) schemes using deep
neural networks (DNNs), called DeepJSCC, provide promising results in wireless image …