Automatic modulation classification is a task that is essentially required in many intelligent
communication systems such as fibre‐optic, next‐generation 5G or 6G systems, cognitive …

Recently, deep learning has been exploited in many fields with revolutionary breakthroughs.
In the light of this, deep learning-assisted communication systems have also attracted much …

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

With the rapid development of deep learning (DL) in recent years, automatic modulation
recognition (AMR) with DL has achieved high accuracy. However, insufficient training signal …

This paper considers a multicasting system in which the base station has a large number of
antennas with cost-effective one-bit digital-to-analog converters and aims to send a common …

We extend the idea of end-to-end learning of communications systems through deep neural
network (NN)-based autoencoders to orthogonal frequency division multiplexing (OFDM) …

This paper demonstrates exceptional performance of approximately 10.0 dB learning-based
gain using the Deep Convolutional Neural Network (DCNN) for demodulation of a Rayleigh …

Recent works have shown that the task of wireless transmission of images can be learned
with the use of machine learning techniques. Very promising results in end-to-end image …

Automatic modulation classification (AMC) plays an important role in intelligent wireless
communications. With the rapid development of deep learning in recent years, neural …

Subsampling of received wireless signals is important for relaxing hardware requirements
as well as the computational cost of signal processing algorithms that rely on the output …