As digital communication technologies continue to grow and evolve, applications for this steady development are also growing. This growth has generated a growing need to look for automated methods for recognizing and classifying the digital modulation type used in the communication system, which has an important effect on many civil and military applications. This paper suggests a recognizing system capable of classifying multiple and different types of digital modulation methods (64QAM, 2PSK, 4PSK, 8PSK, 4ASK, 2FSK, 4FSK, 8FSK). This paper focuses on trying to recognize the type of digital modulation using the artificial neural network (ANN) with its complex algorithm to boost the performance and increase the noise immunity of the system. This system succeeded in recognizing all the digital modulation types under the current study without any prior information. The proposed system used 8 signal features that were used to classify these 8 modulation methods. The system succeeded in achieving a recognition ratio of at least 68% for experimental signals on a signal to noise ratio (SNR = 5dB) and 89.1% for experimental signals at (SNR = 10dB) and 91% for experimental signals at (SNR = 15dB) for a channel with additive white gaussian noise (AWGN)
تاريخ النشر
01/10/2020
الناشر
International Journal of Electrical and Computer Engineering (IJECE)
رقم المجلد
10
رقم العدد
6
ISSN/ISBN
2088-8708
رابط DOI
10.11591/ijece.v10i6.pp5871-5882
الصفحات
5871-5882
الكلمات المفتاحية
Artificial neural networks Digital modulation Smart receivers Software defined radios
د. سعد سفاح الحريشي | Dr. Saad Saffah Hreshee | 1069