Modulation Classifier of Analogue Modulated Signals Based on Method of Artificial Neural Networks

Abstract

Communication signals travelling in space with different modulation types and different 2 KEY FEATURE EXTRACTION frequencies fall in a very wide band. Usually, it is required to identify and monitor these signals for manyIn the proposed modulation classifiers (MC), the key applications. Some of these applications are for civilian features used are derived from three important sphere purposes such as signal confirmation, . interference identification and spectrum management. A qin g pharet -the instantaneous amliude,th new subsystem used in automatic wireless signal i modulation recognition based on ANN is described inThe first key feature, Ymax, is defined by [1], [2] this paper. The signal recognizer being developed consists of five subsystems: (1) adaptive antenna arrays, (2) pre-processing of EM signals, (3) key features Ymax =max |DFT(acn (i))| 2 NS (1 extraction, (4) modulation recognizer and (5) output stage. The choice of maximum value of spectral power N density of the normalized-centred amplitude, standard where s the number of samples per segment and deviation of the absolute value of the centred non-linear acn (i) is the value of the normalized-centred component of the instantaneous phase, standard instantaneous amplitude at time instants deviation of the absolute value of the normalizedcentred instantaneous amplitude, standard deviation of the absolute value of the normalized-centred t=-, (i=1,2, ..., Ns) instantaneous frequency, spectrum symmetry measure fs are used as key features for the analogue modulation recognizer based on the artificial neural networks Ymax represents the maximum value of the spectral (ANNs). The new original structure of the recognizer of power density of the normalized-centred instantaneous analogue signals is described. The modulation amplitude of the intercepted signal. recognizer using the two ANNs with two hidden layers. The results are summarized for real signals with noise The second key feature, C(ap, is defined by [1], [2] and fading.

Applications of MATLAB in Science and Engineering

“…We plan to post future developments of ISPN MATLAB toolbox INTLAB Prototype Tool. (Richterova, 2001), (Richterova & Juracek, 2006) belong to the most frequently exploited and recommended orthogonal transforms. In this chapter, the use of WHT and KLT for the recognition of the frequency shift keying (2-FSK and 4-FSK) signals and the phase shift keying (2-PSK and 4-PSK) signals will be described.…”

“…If more points fall through into the identical node, then is adding the number one next. These output values are standardized and quantized (Richterova, 1997(Richterova, , 1999(Richterova, , 2001, (Richterova & Juracek, 2006). The "phase images" of 2-FSK and 4-FSK signals are presented on Fig.…”

Application of machine learning techniques and empirical mode decomposition for the classification of analog modulated signals

“…In the second group, the classification is obtained by the pattern recognition of some features estimated in the time or frequency domain on the signal under investigation [1] [2][8]- [16]. Moreover, the classification performance of the statistical pattern recognition methods typically decreases along with the increasing ABSTRACT In this article, an automatic Analog Modulation Classifier based on Empirical mode decomposition and Machine learning approaches (AMC-EM) is proposed.…”

New Algorithms for Automatic Modulation Recognition for Analogue Signals Using Multi Features

“…The first feature is the maximum value of the normalized centred instantaneous amplitude of the intercepted signal; the second key feature is the signal spectrum symmetry around the carrier.The performance of this technique was not mentioned. Richterova et al in [8] used the Artificial neural networks and features proposed by [3] to discriminate between analogue modulated signals (AM, FM, DSB, LSB and USB). P. M. Fabrizi et al in [9] proposed a modulation recognizer based on the variations of both the instantaneous amplitude and the instantaneous frequency.…”