Deep learning continues to offer groundbreaking technologies in communications systems
just as it has in a variety of other fields. Despite the notable advancements of technologies …

Deep learning has been a groundbreaking technology in various fields as well as in
communications systems. In spite of the notable advancements of deep neural network …

This paper presents prototyping of a recurrent type neural network (RNN) convolutional
decoder using system-level design specification and design flow that enables easy mapping …

With the flourishing development of wireless communication, further challenges will be
introduced by the future demands of emerging applications. However, in the face of more …

Standard decoding approaches rely on model-based channel estimation methods to
compensate for varying channel effects, which degrade in performance whenever there is a …

A variety of deep learning schemes have endeavoured to integrate deep neural networks
(DNNs) into channel coded systems by jointly designing DNN and the channel coding …

Deep learning has been applied in physical-layer communications systems in recent years
and has demonstrated fascinating results that were comparable or even better than human …

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 …

End-to-end learning of a communications system using the deep learning-based
autoencoder concept has drawn interest in recent research due to its simplicity, flexibility …

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 …