Automatic Modulation Classification using Convolutional Neural Network
With the increasing demands in the field of communication systems evolved the idea of cognitive radio, the design of an intelligent radio capable of sensing the channel conditions and hence deciding the optimal method of connection. Such systems are designed to operate over different channel conditions with different modulation schemes. A modulation classifier is an essential module in such systems and this paper proposes one such design based on convolutional neural networks. The proposed system tries to evaluate the performance of modulation classification over 3 different modulation classes over the Tensor Flow framework.