K-심볼 차동 연산 전처리를 통한 향상된 디지털 변조 분류

초록

Automatic modulation classification(AMC) is a technique of identifying a modulation scheme of the received signal without priori knowledge of the transmitted signal. In commercial and military wireless communication systems, AMC is recognized as an essential element for cognitive radio, spectrum surveillance, and reconnaissance. In this paper, we propose an enhanced modulation classification algorithm with a K-symbol differential preprocessing in the presence of phase and frequency offsets, and analyze its performance. We use cumulant as a feature for modulation classification and extend the number of cumulants used for classification by using additional data generated through the proposed preprocessing. We consider BPSK, QPSK, 8-PSK, 16-QAM, and 64-QAM as candidate modulation schemes, which are mainly used as digital modulation scheme, and verify that the proposed algorithm shows superior performance than the existing one through computer simulations.

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