Blind Signal Modulation Classification Using Constellation Pattern Analysis with Oversampling Factor Alteration
Automatic modulation classification finds its application in many military and civil areas. It is an integral part of cognitive radio and software defined radio technologies. In this paper, LabVIEW based Field Programmable Gate Array (FPGA) implementation of modulation classification algorithm is proposed. Any modulation scheme among BPSK, QPSK, 8PSK, 8QAM, 16QAM and 4ASK is classified by alteration of oversampling factor and further error minimization between extracted constellation and ideal constellation of considered modulation schemes. Study results reveal that the developed method detects the above mentioned modulation schemes reliably above 12 dB SNR in Additive White Gaussian Noise (AWGN) channel. Comparative analysis of the proposed method with existing methods based on higher order statistics, mel-frequency ceptral coefficients and naive based modulation classification shows an overall improvement in classification accuracy.
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