A new method of automatic modulation recognition based on dimension reduction

Abstract

To improve the recognition rate of signal modulation recognition methods under the low Signal-to-noise ratio (SNR), a modulation recognition method is proposed. In this paper, we study an automatic modulation recognition through the Artificial Neural Network (ANN). Implement and design 7 digital modulations are: 2FSK, 4FSK, 8FSK, BPSK, QPSK, MSK and 2ASK. The cyclic spectrum after reducing dimension via Principle Component Analysis (PCA) is chosen as key feature for digital modulation recognizer based on the ANN. We corrupted the signals by additive White Gaussian Noise (AWGN) for testing the algorithm. The simulation results show that the ANN could classify the signals in its current state of development.