Heba A. El-Khobby

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This paper discusses the modulation recognition for OFDM signals in different Signal to Noise Ratio (SNR) and multipath channels. In this paper, the Mel Frequency Cepstral Coefficients (MFCCs) used for feature extraction and the Support Vector Machine (SVM) as classifier or Artificial Neural Network (ANN). Simulation results indicate that the proposed(More)
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(More)
Cloud Computing has continuously tremendous importance in the IT research field. As it is completely rely on sharing both physical and logical resources among numerous users, the concept of security must be considered, and deploying renewable security models must be taken into account. To obtain the highest level of security, some procedures must be(More)
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 with adaptive modulation in Orthogonal Frequency Division Multiplexing (OFDM) systems. The proposed algorithm is verified using(More)
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