Reliable digital communication is a primary workhorse of the modern information age. The
disciplines of communication, coding, and information theories drive the innovation by …

The idea of end-to-end learning of communication systems through neural network (NN)-
based autoencoders has the shortcoming that it requires a differentiable channel model. We …

Watermarking is the process of embedding information into an image that can survive under
distortions, while requiring the encoded image to have little or no perceptual difference with …

Designing codes that combat the noise in a communication medium has remained a
significant area of research in information theory as well as wireless communications …

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

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 …

The recent development in machine learning, especially in deep neural networks (DNN),
has enabled learning-based end-to-end communication systems, where DNNs are …

In this paper, the situation in which a receiver has to execute a task from a quantized version
of the information source of interest is considered. The task is modeled by the minimization …

In this paper, we present a learning scheme for Joint Source-Channel Coding (JSCC) over
analog independent additive noise channels. We formulate the learning problem by …

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