Modulation Classification of MQAM Signals from Their Constellation Using Clustering

Abstract

Nowadays, automatic modulation classification (AMC) plays an important role in both cooperative and non-cooperative communication applications. And most of the approaches for recognition and classification of modulation have been found on modulated signal’s components. However, one of the best methods of modulation classification is the use of the constellation diagram of the received signal. In this paper, a system for modulation classification is developed. A novel method for carrier frequency estimation from the received data is proposed. The method can estimate the carrier frequency exactly by approaching the real frequency illimitably. And an improved method using clustering is also proposed, which can recognize modulated signal’s components only using one clustering radius. The advantages are simple structure and low computation complexity. Simulation results show that the modulation classification method is robust