This chapter is devoted to the use of various neural networks and related learning
algorithms in the channel coding (encoder and decoder) of wireless communications and …

Channel coding is one of the key elements in the physical layer communication system. The
role of channel coding is to introduce redundancy in a controlled manner so that the receiver …

Artificial intelligence (AI)-aided approaches are emerging in solving physical layer
communication problems. In this paper, we focus on applications of deep learning (DL) in …

Wireless Communication has become a critical backbone of the information economy in the
past few decades. In this rapidly improving telecommunications landscape, a crucial role is …

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 …

The usage of artificial intelligence and machine learning in wireless communications is the
stepping stone towards a technological breakthrough in the current limitations of wireless …

Channel Coding has been one of the central disciplines driving the success stories of
current generation LTE systems and beyond. In particular, turbo codes are mostly used for …

Channel coding and modulation are two fundamental building blocks of physical layer
wireless communications. We propose a neural network based end-to-end communication …

In this article, we investigate deep auto-encoders for channel coding to combat the curse of
dimensionality commonly existing in learning based coding. Inspired by convolutional …

Inspired by the recent advances in deep learning, we propose a novel iterative belief
propagation-convolutional neural network (BP-CNN) architecture to exploit noise correlation …