Modulation Recognition Based on Constellation Shape Using TTSAS Algorithm and Template Matching

The automatic recognition of the modulation format of a dete cted signal, the intermediate step between signal detection and demodulation, is a major task of a n intelligent receiver, with various civilian and military applications. Obviously, with no kno wledge of the transmitted data and many unknown parameters at the receiver, such as the signal power , carrier frequency and phase offsets, timing information, etc., blind identification of the modul ation is a difficult task. This becomes even more challenging in real-world. In this paper I develop a nov el algorithm using TTSAS algorithm and pattern recognition to identify the modulation types of the communication signals automatically. I have proposed and implemented a technique that casts modula ti n recognition into shape recognition. Constellation diagram is a traditional and powerful tool fo r design and evaluation of digital modulations. In this paper modulated signal symbols constellatio n utilizing TTSAS clustering algorithm, and matching with standard templates, is used for classificatio n of QAM modulation. TTSAS algorithm used here is implemented by Hamming neural network. The simu lation results show the capability of this method for modulation classification with high accur acy and appropriate convergence in the presence of noise.

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