In wireless communication, signal demodulation under non-ideal conditions is one of the
important research topic. In this paper, a novel non-coherent binary phase shift keying …

In this paper, a novel binary phase shift keying demodulator based on 1-D convolutional
neural network (1-D CNN) is proposed. The utilization of neural networks to detect the …

Demodulation techniques are of central importance for achieving intelligent receiving.
Improvement in demodulation performance enhances the overall performance of a …

In this paper, we investigate deep learning (DL)-enabled signal demodulation methods and
establish the first open dataset of real modulated signals for wireless communication …

In this paper we presented a neural network-based method to demodulate digital signals.
After training with different modulation schemes, the learning-based receiver can perform …

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 …

In this paper we present the symbol and bit error rate performance of the weak signal digital
communications system. We investigate orthogonal multiple frequency shift keying …

In the last few years Machine Learning (ML) has seen explosive growth in a wide range of
research fields and industries. With the advancements in Software Defined Radio (SDR) …

When it comes to studies on smart receiver designs, using machine learning and deep
learning techniques for the development of automatic modulation classifiers as well as …

With the increasingly fierce competition of electromagnetic spectrum, developing intelligent
communication systems that can reconfigure its waveform can effectively improve the …