A basic sequential algorithmic scheme approach for classification of modulation based on neural network

Abstract

In this paper modulated signal symbols constellation utilizing TTSAS clustering algorithm, which is a specific kind of BSAS clustering, 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.