An Algorithm for Analog Modulation Classification

Radio engineering

  • A. M. Tantushyan Public services regulatory commission of RA (PSRC)
Keywords: artificial neural network, analog modulations, key features, automatic modula-tion recognition.


Research in automatic modulation classification systems has been carried out for a long period of time and many methods and classifiers are presented for both analog and digital modulations. The purpose of such systems is to properly recognize the unknown signal’s mod-ulation type and transfer it to the demodulator in order to fully recover the modulating signal. The program code developed in LabVIEW graphical programming environment represents a new technical solution of the analog modulation classification problem. It enables the usage of fast-operating hardware for real-time testing. The description of automatic modulation recogni-tion algorithm for analog modulations programmed in LabVIEW is presented in this article. Among analog modulations especially double sideband (DSB), single sideband (SSB) and fre-quency modulated (FM) signals have been considered.
The LabVIEW code consists of three parts, each maintaining specific tasks. The first part has to implement the task of a receiver and process, the received signal and extract key fea-tures, but here only simulated signals have been considered. The second part represents the algorithm of the classifier and the third part is the demodulator block. After simulating a signal and extracting the key features, their values are passed to the classifier’s inputs. An artificial neural network was chosen as a classifier for this task. The network implements self-learning before testing and based on the learning results, classifies the current signal modulation type.
Afterwards, testing was carried out, and the results are shown in this paper.

Author Biography

A. M. Tantushyan, Public services regulatory commission of RA (PSRC)

Tantushyan Aram Mikael
PhD student, “Institute of Radiophysics and Electronics” NAS RA; leading specialist, Public Services Regulatory Commission