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In this paper, the robust QAM classification method against phase offsets has been proposed. In the proposed method, the amplitude and the square cosine moments are used for the classification. The classification error probability has been examined for 16QAM and 64QAM. Simulation results have shown that the proposed method gives the superior classification performance to the amplitude moments method.
A new modulation classification method for M-ary QAM (MQAM) is proposed in this paper. Our method employs two dimensional decision variable composed of amplitude and cosine moments. Numerical results of the classification error probability show that the method presents superior classification performance for MQAM compared with amplitude moments or cosine moments approach.
In this paper, QAM classification based on cosine moments is analyzed. The cosine moments give poor performance for QAM classification because of a large phase noise of small amplitude signals. In the method, these small amplitude signals are not employed for the classification. An analytical approach for the classification error probability is presented for the cosine moment method. Although small...
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