CNN-Based Modulation Classification for OFDM Signal

Abstract

Automatic modulation classification (AMC) is one of the important parts in cooperative and noncooperative contexts. This paper approaches the AMC problem by using deep learning. We propose a convolutional neural network (CNN)-based AMC to classify the modulation type of received orthogonal frequency division multiplexing (OFDM) signal and analyze its classification performance. CNN model is trained by using received OFDM signals for different modulation types and signal-to-noise ratios, and then classification accuracy is validated through computer simulations.