Signal Modulation Recognizer Based on Method of Artificial Neural Networks
نویسنده
چکیده
Communication signals travelling in space with different modulation types and different frequencies fall in a very wide band. Usually, it is required to identify and monitor these signals for many applications. Some of these applications are in civilian purposes such as signal confirmation, interference identification and spectrum management. this paper described the new original configuration of subsystems for the automatic modulation recognition of digital and analog signals. The signal recognizer being developed consists of five subsystems: (1) adaptive antenna arrays, (2) pre-processing of EM signals, (3) key features extraction, (4) modulation recognizer and (5) output stage. The choice of maximum value of spectral power density of the normalized-centred amplitude, standard deviation of the absolute value of the centred non-linear component of the instantaneous phase, standard deviation of the absolute value of the normalized-centred instantaneous amplitude, standard deviation of the absolute value of the normalized-centred instantaneous frequency, spectrum symmetry measure as key features for the digital and analogue modulation recognizer based on the artificial neural networks (ANNs). The new original structure of the recognizer of digital and analogue signals is described. The modulation recognizer uses two ANNs with two hidden layers. The results are summarized for real EM signals.
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