Recently, deep learning (DL) is an innovative machine learning (ML) technique that has
gained the outstanding achievements in computer vision and natural language processing …

Natural signals are inherently comprised of two components, real and imaginary
components. Due to recent successes and progress in Deep Learning, specifically …

This paper enhances the performance and training of the Turbo Autoencoder (TurboAE), an
end-to-end jointly trained neural channel encoder and decoder. A novel interleaver for …

Automatic modulation recognition (AMR) plays a vital role in non-cooperative
communication systems, which is an important technological component of blind signal …

Deep learning-based joint source-channel coding (DJSCC) is expected to be a key
technique for {the} next-generation wireless networks. However, the existing DJSCC …

Automatic modulation classification (AMC) is an impressive technology, which is widely
used in military and civilian fields. Recently, deep learning-based AMC (DL-AMC) methods …

Designing channel codes is one of the core research areas for modern communication
systems. Canonical channel codes asymptotically achieve near-capacity performance under …

Automatic modulation classification (AMC) identifies a received signal's modulation scheme
without prior knowledge of the intercepted signal, which enables significant applications in …

We consider the design of efficient neural-network based algorithms, referred to as neural
decoders, for decoding linear and non-linear block codes, such as Hamming and constant …