Demodulation is a fundamental and critical function of communication systems. Traditional
demodulation methods are designed for specific modulation schemes, which require …

In recent years, deep learning is becoming more and more popular. It has been widely used
in image recognition, automatic speech recognition and natural language processing. In the …

Blindly decoding a signal requires estimating its unknown transmit parameters,
compensating for the wireless channel impairments, and identifying the modulation type …

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 …

The process of demodulating an unknown wireless communication signal without
knowledge of the channel state and modulation type is called the dual-blind demodulation …

In this paper, we propose high performance blind modulation classification (BMC) technique
based on deep neural network (DNN) for fading channels. First, we provide the large and …

State-of-the-art modulation classifiers often require matching channel model and perfect
knowledge of channel state information to mitigate lose in classification accuracy. In this …

In this study, an algorithm to blind and automatic modulation classification has been
proposed. It investigates combined machine leaning and signal feature extraction in order to …

Blind modulation classification is widely used in various military and civilian applications.
Characterized by its exemption from likelihood calculation and the ability of using well …

Blind System Identification (BSI) is a major pattern recognition task in many fields, including
digital communication systems. Recently, many machine learning techniques have been …