xushang / automatic-digital-modulation-detection-

This repository presents the code for digital modulation detection in Communication networks

Automatic-Digital-Modulation-Detection-

This repository presents the code for digital modulation detection in Communication networks.

In this work, we develop a new automatic modulation recognition system that maintains a simple structure and provides higher accuracy. Different types of modulated signal simulated by using the OFDM (Orthogonal Frequency Division Multiplexing). The modulation techniques like QPSK, BPSK, 8PSK, and 16PSK are used for classification. There are three phases of our proposed work: features extraction, features selection, and modulation classification. In the first step, the OFDM signal is simulated. We extract a total of twelve features from the simulated signal. The block diagram is as:

Problem Statement

Following points are considered as the problem statement;

1. The automatic modulation detection is necessary for the communication system as allows the blind detection of modulation and lower the circuitry cost of designing the different demodulators at receiver. The Noise in the medium also keeps on changing the behavior of the modulated signal. The automatic modulation classification makes the communication receiver adaptive.
2. The automatic modulation detection work is based on various signal features which might not contribute towards classification accuracy and just increase the overhead. To get the optimal set of features which only contribute to accuracy, feature selection is an essential step.

The complete description can be checked at https://free-thesis.com/product/automatic-digital-modulation-detection-by-neural-network/