Modulation Recognition

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Automatic Modulation Recognition Using Wavelet Transform and Neural Networks in Wireless Systems

Automatic Modulation Recognition Using Wavelet Transform and Neural Networks in Wireless Systems

Copyright © 2010 K. Hassan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Modulation type is one of the most important characteristics used in signal waveform identification. In this paper, an algorithm for automatic digital modulation recognition is proposed. The proposed algorithm is verified using higher-order statistical moments (HOM) of continuous wavelet transform (CWT) as a features set. A multilayer feed-forward neural network trained with resilient backpropagation learning algorithm is proposed as a classifier. The purpose is to discriminate among different M-ary shift keying modulation schemes and the modulation order without any priori signal information. Pre-processing and features subset selection using principal component analysis is used to reduce the network complexity and to improve the classifier’s performance. The proposed algorithm is evaluated through confusion matrix and false recognition probability. The proposed classifier is shown to be capable of recognizing the modulation scheme with high accuracy over wide signal-to-noise ratio (SNR) range over both additive white Gaussian noise (AWGN) and different fading channels.
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Intra pulse modulation recognition using short time ramanujan Fourier transform spectrogram

Intra pulse modulation recognition using short time ramanujan Fourier transform spectrogram

Recently, the concept of Ramanujan Fourier Trans- form(RFT) based time-frequency transform, namely Short-time Ramanujan Fourier transform(ST-RFT) has been investigated owing to the good immunity to noise interference of RFT functions [16–18]. Following this, the time-frequency analysis of signals based on RFT was considered in a letter by Sugavaneswaran [19]. Their re- search indicates that in the presence of noise this class of transforms has lower effect in comparison to Discrete Fourier Transform (DFT) based time-frequency trans- forms. Consequently, regarding the noise robustness, the ST-RFT is more efficient than the traditional DFT based time-frequency transform, and is a promising solution for intra-pulse modulation recognition under low SNR.
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An approach to the modulation recognition of MIMO radar signals

An approach to the modulation recognition of MIMO radar signals

The concept of multiple-input multiple-output (MIMO) radar, which comes from communication system, has drawn considerable attention in recent years from both re- searchers and practitioners [1]. It builds a bridge between the research of radar and communication. MIMO radar is generally divided into two categories, one is statistical MIMO radar with widely separated antennas, and the other is coherent MIMO radar with co-located antennas. In both categories of MIMO radar system, multiple trans- mit antennas are employed to emit specific waveforms and multiple receive antennas process the reflected signals jointly. MIMO radar offers quite a lot of advantages, such as more degrees of freedom, higher resolution, and sensi- tivity and better parameter identifiability [2-4]. These ad- vantages mostly result from waveform diversity. Due to the waveform diversity, intercepted signals in reconnaissance receiver are multi-carrier signals. Accordingly, signal detec- tion, parameter estimation, and modulation recognition are vastly different from single-carrier (SC) signals adopted by conventional radars. As a result, it poses an emerging and powerful challenge in electronic countermeasures.
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Research on Modulation Recognition Algorithm of Submarine Modulation Signal

Research on Modulation Recognition Algorithm of Submarine Modulation Signal

communication signals through some means. The modulation mode of decision signals provides useful information for signal analysis, identification, processing, and anti-jamming. It is widely used in many areas of civil and military applications such as spectrum monitoring, interference identification, and electronic countermeasures. In the complex electromagnetic environment, the submarine's good concealment and greater assault power make it play an important role in the modern informationized battlefield. Therefore, it is of great practical significance to modulate the signals of submarine targets. The automatic modulation recognition technology, which includes signal detection, feature parameter extraction, classification recognition, etc., can overcome the deficiencies of the artificial method, and has a strong inhibitory effect on external interference such as error estimation, noise, and fading. With the development of communication technology, automatic modulation recognition technology has been well applied and developed with higher accuracy and robustness.
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Blind Modulation Recognition in Wireless MC CDMA Systems Using a Support Vector Machine Classifier

Blind Modulation Recognition in Wireless MC CDMA Systems Using a Support Vector Machine Classifier

Automatic Digital Modulation Recognition (ADMR) is becoming an interesting problem with various civil and military applications. In this paper, an ADMR algorithm in Multi-Carrier Code Division Multiple Access (MC-CDMA) systems using Discrete Transforms (DTs) and Mel-Frequency Cepstral Coefficients (MFCCs) is proposed. This algorithm uses various DT techniques such as the Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Discrete Sine Transform (DST) with MFCCs to extract features from the modulated signal and a Support Vector Machine (SVM) to classify the modulation orders. The proposed algorithm avoids over fitting and local optimal problems that appear in Artificial Neural Networks (ANNs). Simulation results shows the classifier is capable of recognizing the modulation scheme with high accuracy up to 90% - 100% using DWT, DCT and DST for some modulation schemes over a wide Signal-to-Noise Ratio (SNR) range in the presence of Additive White Gaussian Noise (AWGN) and Rayleigh fading channel, particularly at a low Signal-to-Noise ratios (SNRs).
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An Approach of Modulation Recognition Using 4th Order Cyclic Cumulants Vector of Digital Signal for Cognitive Radio

An Approach of Modulation Recognition Using 4th Order Cyclic Cumulants Vector of Digital Signal for Cognitive Radio

For modulation recognition, features of digital signal should be extracted firstly, then the modulation is confirmed by some recognition method. In feature description research area, some former research applied temporal statistical features for modulation recognition, such as instantaneous amplitude, phase and frequency[2]. In[3], Tang et al. utilized moment and normalized kurtosis as feature for modulation recognition. Other researchers extract features based on some properties of modulated signal, such as cyclostationary features[4], high order cumulants feature[5], spectral correlation features[6], et al.
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Research on modulation recognition with ensemble learning

Research on modulation recognition with ensemble learning

mapping the time-series signals to feature fields, and the process of recognition just depends on the featured parameters. Compared with the former, pattern recog- nition occupies the advantage, an easy engineering im- plementation, and has a widespread application field. Generally, a large amount of data sets and training sets are employed to train the classifier, and then, a series of rather small sets, also called testing sets, try out the performance of the classifier. Above content has already displayed the primary steps for pattern recog- nition. However, there still exists a critical key issue of how to determine the classifier. A superior classifier can improve the overall recognition results, while a poor one will pull down the classification performance. A number of classifiers have been published, but the results are barely satisfactory under low signal to noise ratios (SNRs). To ameliorate the current state, we use the ensemble algorithm instead of single classifier. These algorithms, such as bagging and boosting, have been revealed more significant advantages than signal classifier [1–3, 33–37].
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Signal space based adaptive modulation for software radio

Signal space based adaptive modulation for software radio

Automatic modulation recognition and scheme switching enables correct demodulation of a received signal without apriori modulation scheme knowledge. A software receiver implementation facilitates a much more flexible and relatively inexpensive application design. This is important for dynamically changing the function of the radio, and for reacting to changes in the intercepted signal such as a change of modulation scheme employed, for example. Signal space representation of quadrature components of an intercepted signal is a graphical means of monitoring channel quality variations. Constellation diagrams are commonly used to assess the underlying signal structure of a signal. The mean excursion of received signal points about ideal signal points on a constellation diagram may be used as a metric to determine whether the employed modulation scheme can be supported over the time-varying channel.
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Hallmarks of glycosylation in cancer

Hallmarks of glycosylation in cancer

The hallmarks of cancer comprise biological capabilities acquired during the multi-step development of cancer that allow cancer cells to survive, proliferate and disseminate [1]. Glycosylation is frequently cited as hallmark of cancer but was notably absent from both the original hallmarks and from the updated next generation cancer hallmarks. Here we argue that the process of glycosylation is an enabling characteristic that is causally associated with the acquisition of all the proposed cancer hallmark capabilities (Figure 1), and conversely that the glycan composition of cancer cells can in turn be influenced by the other hallmarks. Glycans have roles in cancer cell signalling, tumour cell dissociation and invasion, cell-matrix interactions, angiogenesis, metastasis and immune modulation. Recognition of the widespread applicability of glycosylation to the cancer hallmarks will increasingly affect the development of new means to treat human cancer.
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Fuzzy inference system based adaptive modulation scheme for optical wireless communication

Fuzzy inference system based adaptive modulation scheme for optical wireless communication

Constructing the rules using the graphical Rule Editor interface is fairly self-evident. Based on the descriptions of the input and output variables defined with the FIS Editor, the Rule Editor for Adaptive DAPPM modulation technique was developed. Fuzzy logic incorporated a simple rule-based “If X and/or Y then Z” approach to solve control problems rather than attempting to model a system mathematically. The rules are flexible to add, delete or change using the rule editor. An example of five rules that are already sets is shown in Figure 9.

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Highlights on signals from Dark Matter particles

Highlights on signals from Dark Matter particles

To obtain a reliable signature for the presence of DM particles in the galactic halo, it is necessary to exploit a suitable model independent signature. With the present technology, one feasible and able to test a large range of cross sections and of DM particle halo densities, is the so-called DM annual modulation signature [1]. The annual modulation of the signal rate originates from the Earth revolution around the Sun. In fact, as a consequence of its annual revolution around the Sun, which is moving in the Galaxy traveling with respect to the Local Standard of Rest towards the star Vega near the constellation of Hercules, the Earth should be crossed by a larger flux of DM particles around ∼ 2 June (when the Earth orbital velocity is summed to the one of the solar system with respect to the Galaxy) and by a smaller one around ∼ 2 December (when the two velocities are subtracted). Thus, this signature has a different origin and peculiarities than effects correlated with seasons (consider the expected value of the phase as well as the other requirements listed below). This DM annual modulation signature is very distinctive since the effect induced by DM particles must simultaneously satisfy all the following requirements: (1) the rate must contain a component modulated according to a cosine function; (2) with one year period; (3) with a phase that peaks roughly around ∼ 2nd June; (4) this modulation must be present only in a well-defined low energy range, where DM particles can induce signals; (5) it must be present only in those events where just a single detector, among all the available ones in the used set-up, actually “fires” (single-hit events), since the probability that DM particles experience multiple interactions is negligible; (6) the modulation amplitude in the region of maximal sensitivity has to be < ∼ 7% in case of usually adopted halo distributions, but it may be significantly larger in case of some particular scenarios such as e.g. those in Ref. [2, 3]. This signature is model independent and might be mimicked only by systematic e ff ects or side reactions able to simultaneously satisfy all the requirements given above; no one is available. At present status of technology it is the only DM model independent signature available in direct DM investigation that can be effectively exploited.
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Cascaded H-Bridge Inverter with Minimum Switches Using Hybrid Modulation Technique

Cascaded H-Bridge Inverter with Minimum Switches Using Hybrid Modulation Technique

where A is an SSP, B is an FPWM, C’ is an MSPWM for cell-I and D’ is an MSPWM for cell-II. If SSP A = 1, then S1, S2, S1’, and S2’ are operated with MSPWM, while S3, S4, S3’, and S4’ are operated at FPWM. If SSP A = 0, then S1, S2, S1’, and S2’ are operated at FPWM, while S3, S4, S3’, and S4’ are operated with MSPWM. Since A is a sequential signal, the average switching frequency amongst the four switches is equalized. Voltage stress and current stress of power switches in each cell is inherently equalized with this modulation.

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Stable distributions as noise models for molecular communication

Stable distributions as noise models for molecular communication

Abstract—In this work, we consider diffusion-based molecular communication timing channels. Three different timing channels are presented based on three different modulation techniques, i.e., i) modulation of the release timing of the information particles, ii) modulation on the time between two consecutive information particles of the same type, and iii) modulation on the time between two consecutive information particles of different types. We show that each channel can be represented as an additive noise channel, where the noise follows one of the subclasses of stable distributions. We provide expressions for the probability density function of the noise terms, and numerical evaluations for the probability density function and cumulative density function. We also show that the tails are longer than Gaussian distribution, as expected.
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In this paper, an MC6809 microprocessor- based control of a PWM single phase voltage source inverter supplying an induction heating tank load has been presented. Three single pulse per half cycle modulation methods of the inverter output voltage have been described. These are the zero voltage, the zero current and the hybrid single pulse modulation methods. These basic three modulation techniques have been implemented using the MC6809 microprocessor and appropriate

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Phase object pattern recognition by optical correlation using a liquid crystal display for spatial phase modulation

Phase object pattern recognition by optical correlation using a liquid crystal display for spatial phase modulation

A commercial Liquid Crystal Display (LCD) is utilised as an optical Fourier plane filter medium, affording the high spatial resolution of 'purpose made' spatial light modulators (SLMs), but at lower cost and with simple drive signal requirements. While LCDs are designed as intensity modulators, it is known that in the spatial frequency domain, phase manipulation is more effective than intensity manipulation. The LCD's polariser and analyzer orientation is engineered to provide up to 229° of phase modulation (despite an LC layer thickness of less than 4.5}im) with insignificant coupled intensity modulation. A model developed in the UCL/Sira research group to show complex modulation as a function of polariser / analyzer configuration is experimentally evaluated. An improvement to the model showing the importance of including effective LC cell capacitance is also detailed. The LCD system's response to high spatial frequency images is investigated, and an algorithm, devised to process images prior to display, is described. While proving useful for visual display purposes, it was not found suitable for correlation filter display.
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A Multilevel Cascaded Inverter for Unbalanced DC Source using Carrier Based Neutral Voltage Modulation Strategy

A Multilevel Cascaded Inverter for Unbalanced DC Source using Carrier Based Neutral Voltage Modulation Strategy

and the dependent vectors. Unlike traditional three-phase half bridge inverters, the independent vectors can be fully applied in a switching period because the dc links in each of the three phases are separated in the given system. It should be noted that the maximum voltage is decided by the dependent vectors in the entire voltage vector space. Now, let us consider the case when a three-phase load is supplied by unequal dc links. Vdc_a has a lower value than the others. In Fig. 5.6(b), all three dc links have different voltages. As it can be seen in Fig. 5.6, the original shape of the hexagon is distorted in both cases. As shown in Fig. 5.6, the radius is changed as the hexagon distorts, and the achievable linear modulation range is also altered. Here, the maximum amplitude of the phase voltage Vph_max in the linear modulation range is defined as
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Toward a dynamical systems analysis of neuromodulation

Toward a dynamical systems analysis of neuromodulation

a function of the sum of the synaptic inputs. Pollack thought that connections that multiplied the sum of the synaptic inputs were equally as important. Further- more he believed that full Turing-complete computabil- ity could not be realized without such connections. This was later shown not to be the case (Siegelmann & Son- tag, 1995). Nevertheless, Pollack goes on to state that “multiplicative connections remain a critical and under appreciated component of neurally inspired computing” (Pollack, 1999). Although the addition of multiplicative connections may not confer new functionality on simple additive networks, they may alter what behaviour is eas- ily obtained, and hence network evolvability. The next section will look closely at the different types of param- eter modulation possible in our augmented FHN model.
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An Analysis and Detection Results of Spatial Modulation using Modulation Schemes

An Analysis and Detection Results of Spatial Modulation using Modulation Schemes

In this paper we are comparing Maximum Ratio Combining scheme i.e. MRC scheme and ML detection scheme and thus analyzing there BER and reduction in complexity for GSM. MIMO systems are the key features for achieving capacity gain and diversity gain depending on the channel condition .In this paper, we have also compared these MRC and ML detection scheme by comparatative analysis of the Bit Error Rate performance of various modulation schemes. The simulation results helps us to analyze that it is possible to reduce the BER and helps to obtain good SNR by MRC detection scheme. These modulation scheme are using MRC and ML detection schemes.
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Co receptor CD8 mediated modulation of T cell receptor functional sensitivity and epitope recognition degeneracy

Co receptor CD8 mediated modulation of T cell receptor functional sensitivity and epitope recognition degeneracy

T-cell antigen recognition can be expressed in terms of its func- tional sensitivity (18). One of the main determinants of functional sensitivity is the rate at which a single agonist copy elicits TCR triggering. Functional sensitivity depends on bio-molecular para- meters such as the TCR/pMHCI on-rate and off-rate. The mole- cular kinetics at the T-cell:antigen-presenting cell (APC) interface determine this relationship. This kinetic theory resolves the long- standing controversy over whether T-cell activation is governed by affinity or off-rate (cf. (19, 20)); the theory shows that both parameters play a role, but in the so-called MHC-limited regime, the off-rate is the main governing factor. However, the on-rate and the off-rate together determine whether or not the kinetics is MHC-limited (21–23).
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New Approach for Network Modulation in Cooperative Communication

New Approach for Network Modulation in Cooperative Communication

In this paper, we are proposing a new approach to improve wireless network by using network modulation. It is based on software bit remapping, NM scheme can be implemented using existing transceiver hardware. Modulation type is chosen on the basis of channel quality to maximize the data rate under the constraint that the Bit Error Rate (BER) is below a threshold. If we discuss about signal to noise ratio, is different for different channels. In this paper we are presenting a three node scenario. These three nodes are source, destination and relay. Here one node works as a relay node between source and destination nodes. According to SNR information of different channel in the network a method is presented to choose best scalable modulation scheme to maximize the network throughput.
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