Abstract
Based on the features extracted from generalized autoregressive (GAR) model parameters of the received waveform, and the use of multilayer perceptron(MLP) neural network classifier, a new digital modulation recognition method is proposed in this paper. Because of the better noise suppression ability of the GAR model and the powerful pattern classification capacity of the MLP neural network classifier, the new method can significantly improve the recognition performance in lower SNR with better robustness. To assess the performance of the new method, computer simulations are also performed.
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Lu, M., Xiao, X. & Li, L. A new digital modulation recognition method using features extracted from GAR model parameters. J. of Electron.(China) 16, 244–250 (1999). https://doi.org/10.1007/s11767-999-0022-6
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DOI: https://doi.org/10.1007/s11767-999-0022-6