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 …

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 …

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 …

Upcoming modern communications are based on 5G specifications and aim at providing
solutions for novel vertical industries. One of the major changes of the physical layer is the …

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 …

Deep neural network (DNN)-based channel decoding is widely considered in the literature.
The existing solutions are investigated for the case of hard output, ie when the decoder …

The recent development of deep learning methods demonstrates a new insight to optimize
the decoding of linear codes. In this paper, we survey the typical neural network decoding …

The design of optimal channel codes with computationally efficient Forward Error Correction
(FEC) codes remains an open research problem. In this paper, we explore optimal channel …

In the last decade, deep neural networks (DNNs) have shown impressive results in various
fields such as image classification, speech recognition, or playing the abstract strategy …