Identification of digitally modulated signal used in cognitive radio network -A survey

摘要

To analyze any communication signal, knowing the type of modulation is an important topic. Hence, Adaptive modulation identification has gained great importance in various communication systems such as military communication systems, software radios, and cognitive radios (CR) for various purposes including adaptive communication and spectrum monitoring. Applying a machine learning algorithm and subsequently computing the distinguishing features of an input data set is a well-known way to differentiate these signals. What is proposed, therefore, is a recognition system capable of classifying digital modulation signals (QAM and QPSK). As a matter of fact, it is an artificial neural network (ANN) that is used to distinguish between the two types mentioned above.