C24. Automatic modulation recognition in wireless systems using cepstral analysis and neural networks

Abstract

Modulation type is one of the most important characteristics used in signal waveform identification for wireless communications. In this paper, a cepstral algorithm for Automatic Digital Modulation Recognition (ADMR) is proposed. This algorithm uses Mel-Frequency Cepstral Coefficients (MFCCs) to extract the features of the modulated signal and a multi-layer feed-forward Artificial Neural Network (ANN) to classify the modulation type and its order. The proposed algorithm is capable of recognizing the modulation scheme with high accuracy in the presence of Additive White Gaussian Noise (AWGN) over a wide Signal-to-Noise Ratio (SNR) range.