Modulation Classifier for Primary User Detection

Spectrum scarcity issue is being addressed by using dynamic spectrum sharing of cognitive radio. Primary user detection is the primary task in cognitive radio. Modulation Classification can be applied as the vital principle in this article to identify the particular primary user radio type. A novel method to classify the modulation type has been suggested in this paper by using the neural network algorithm. The entire system is implemented using a Software Defined Radio platform (NIUSRP). The system will classify the type of modulation and which is used to detect the presence of the primary user for the cognitive radio application. In this paper, three different modulation type has been implemented in USRP SDR in real-time. The primary purpose of implementing the modulation classification algorithm is to identify the existence of a signal at a given location at a given frequency band at the given time.