QAM Modulation Classification using Constellation diagram based on TTSAS Algorithm and Template Matching

Recently the problem of modulation classification has received much attention in military and commercial applications. Various approaches introduced to solve this problem. Most of these approaches has been based on some special characteristics of received signal which are resolvable for various types of modulations. In this paper modulated signal symbols constellation utilizing TTSAS clustering algorithm and matching with standard templates, is used for classification of QAM modulation. TTSAS algorithm used in this paper is implemented by Hamming neural network. The simulation results show the capability of this method for modulation classification with high accuracy and appropriate convergence in the presence of noise.