Daldal, Nihat2021-06-232021-06-2320200378-43711873-2119https://doi.org/10.1016/j.physa.2019.122836https://hdl.handle.net/20.500.12491/10571In this study, the estimation of modulation type and demodulation data from Quadrate type QASK, QFSK and QPSK modulation signals, which are widely used in digital modulation types, has been performed. For this purpose, modulation signals with 1-byte length ranging from 0 to 255 have been obtained for QASK, QFSK and QPSK modulations from multi-level modulation methods. An automatic 3-stage software layer has been developed for the estimation of data from QASK, QFSK and QPSK modulated signals. Quadrate type modulation signals have 4 carrier frequencies. In the software layer, firstly, the modulation signals have been divided into 4 equal parts, and each piece's period has been determined. Moreover, by applying Fourier analysis to each part, amplitude and phase information from the signal has been extracted for the first 10 harmonics. With Fourier analysis, reference signals for QASK, QFSK, and QPSK modulation were generated according to the amplitude, frequency and phase information of each part. Error matrices have been created by comparing each part of the data to the reference signals to be demodulated. According to the least faulty matrices, the binary data value of the signal piece has been found, and then the type of modulation has been determined by comparing the errors totals. Finally, the baseband demodulation data obtained in 4 separate logic 2 bits have been converted to decimal. In this way, the type of any modulation signal could be automatically determined and so that the base band data could be obtained successfully by the developed method. The proposed hybrid signal processing can be easily adapted to microcontroller systems in the real world. (C) 2019 Elsevier B.V. All rights reserved.eninfo:eu-repo/semantics/closedAccessDigital ModulationQuadrate ModulationDemodulationModulation ClassificationSignal ProcessingA novel demodulation method for quadrate type modulations using a hybrid signal processing methodArticle10.1016/j.physa.2019.1228365402-s2.0-85076207897Q2WOS:000506711900084Q2