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 …

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

Aiming at the problem of signal demodulation under noise interference channel, a signal
recognition method using deep learning is proposed. The signal demodulation is completed …

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 …

In recent years, extensive research has been done to obtain better demodulation
performance by combining signal demodulation with deep learning algorithms, such as …

With the unprecedented availability of computing and data resources, there has been a
widespread trend in using machine learning techniques in the field of communication as …

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

Blind recognition is of great significance in non-cooperative communication research. In
practical communication scenarios, multistage signal processing schemes are usually used …

In recent years, deep learning is becoming more and more popular. It has been widely
applied to fields including image recognition, automatic speech recognition and natural …

Blind identification of modulation and channel coding parameters is a very important
research topic in civil-military communication systems. The traditional algorithm is mainly …