The method of improving the dynamic range of analog-digital conversion of phase jitter signals in telecommunications systems

Bortnyk, Gennadiy; Vasylkivskyi, Mikola; Kychak, Vasyl

doi:10.1109/ukrmico.2016.7739630

Cited by 8 publications

(5 citation statements)

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“…When employing classical methods and models for assessment of signal strength in wireless channels, there occurs high complexity while taking into consideration the large number of impact factors. In turn, in order to reduce the complexity, it is possible to apply a multitude of models and methods aimed at solving specific problems [10] or which are used at individual nodes and stages of signal conversion [11]. However, based on the obtained experimental data, on can see that the spatial signal distribution demonstrates fluctuations with typical maxima and minima.…”

Section: Discussion Of Research Results and Constructed Modelsmentioning

confidence: 99%

Construction of mathematical models for the estimation of signal strength at the input to the 802.11 standard receiver in a 5 GHz band

Mykhalevskiy

2018

EEJET

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Section: Discussion Of Research Results and Constructed Modelsmentioning

confidence: 99%

Construction of mathematical models for the estimation of signal strength at the input to the 802.11 standard receiver in a 5 GHz band

Mykhalevskiy

2018

EEJET

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“…На практиці виникає необхідність використання методів ЦОС у реальному масштабі часу. Проблематика ЦОС у реальному часі зумовлена обмеженою швидкодією програмно-апаратних засобів радіоконтролю [1].…”

Section: постановка проблеми у загальному вигляді та її зв'язок із ва...unclassified

“…ДПФ першої підпослідовності (1). На базі відомого ДПФ (1) необхідно знайти ДПФ нової підпослідовності, що отримана шляхом подовження початкової підпослідовності на m відліків справа та вилученням її перших відліків.…”

Section: виклад основного матеріалуunclassified

“…Аналізуючи вираз (3) можна стверджувати, що у квадратних дужках виразу знаходиться та ж сума, що й у правій частині виразу (1). Враховуючи це, а також взявши до уваги властивість періодичності повертальних множників ДПФ, вираз для знаходження…”

Section: виклад основного матеріалуunclassified

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Spectral-Covariation Method of Classification of Radio Signals

BORTNYK,

KYRYLYUK

2023

Herald KhmNU.TS

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The paper proposes a high-performance method of radiosignal classification based on spectral-covariance evaluation of signals. At the same time, multi-stage processing of overlapping subsequences of readings of the investigated radiosignal in the time and frequency domain is carried out. At the first stage, it is proposed to evaluate the parameters of the radiosignal based on the found power spectral density of the investigated signal. To determine the spectral density of the radiosignal, subsequences of readings obtained from the array of input readings of the investigated signal are formed. The maximum shift between two adjacent subsequences is chosen, that is, the initial realization of the signal is presented in the form of overlapping subsequences. Taking into account that two adjacent subsequences have part of common processed readings, the paper proposes an expression that for each new subsequence of input readings would take into account the coefficients of the discrete Fourier transform, which were determined for the previous subsequence of the input signal. During the following stages, the shape of the spectrum of the analyzed radiosignal is compared with the spectrum samples specified by the operator of the radiocontrol system. Comparison of the spectrum of the investigated radiosignal and the spectral mask is based on the determined correlation coefficient. The approximation of the value of the correlation coefficient to unity characterizes the degree of linear relationship between the spectrum of the signal and the mask. This makes it possible to determine the type and positions of radiochannels based on the obtained sequence of correlation coefficient values for different shifts of the spectral mask. The analysis of the effectiveness of the proposed method confirmed that thanks to the developed method, it is possible to increase the productivity of the spectral-covariance evaluation of radio signals by 2.0Г·8.9 times, depending on the volume of the analyzed implementation of the radiosignal and the number of overlapping subsequences. The maximum performance factor is achieved when the initial implementation of the radiosignal is divided into 64 overlapping subsequences. The proposed method can be used in automated radiotechnical control systems to monitor the radiosituation in real time.

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“…Accordingly, EEG amplitude signals are sometimes not very reliable, and signals of instantaneous EEG phases can be more informative [74]. Beyond their application to EEG signals [38,[75][76][77][78], instantaneous phase signals are used in different fields of signal processing: telecommunication systems [79,80], electrocardiography [81,82], geophysics [83,84], among others. The instantaneous phase can be determined by means of several techniques, e.g., the Hilbert transform [85], complex wavelet transform [86] or the marker event method [87,88].…”

Section: Introductionmentioning

confidence: 99%

Phase irregularity: A conceptually simple and efficient approach to characterize electroencephalographic recordings from epilepsy patients

Espinoso

Andrzejak

2022

Phys. Rev. E

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The severe neurological disorder epilepsy affects almost 1% of the world population. For patients who suffer from pharmacoresistant focal-onset epilepsy, electroencephalographic (EEG) recordings are essential for the localization of the brain area where seizures start. Apart from the visual inspection of the recordings, quantitative EEG signal analysis techniques proved to be useful for this purpose. Among other features, regularity versus irregularity and phase coherence versus phase independence allowed characterizing brain dynamics from the measured EEG signals. Can phase irregularities also characterize brain dynamics? To address this question, we use the univariate coefficient of phase velocity variation, defined as the ratio of phase velocity standard deviation and the mean phase velocity. Beyond that, as a bivariate measure we use the classical mean phase coherence to quantify the degree of phase locking. All phase-based measures are combined with surrogates to test null hypotheses about the dynamics underlying the signals. In the first part of our analysis, we use the Rössler model system to study our approach under controlled conditions. In the second part, we use the Bern-Barcelona EEG database which consists of focal and nonfocal signals extracted from seizure-free recordings. Focal signals are recorded from brain areas where the first seizure EEG signal changes can be detected, and nonfocal signals are recorded from areas that are not involved in the seizure at its onset. Our results show that focal signals have less phase variability and more phase coherence than nonfocal signals. Once combined with surrogates, the mean phase velocity proved to have the highest discriminative power between focal and nonfocal signals. In conclusion, conceptually simple and easy to compute phase-based measures can help to detect features induced by epilepsy from EEG signals. This holds not only for the classical mean phase coherence but even more so for univariate measures of phase irregularity.

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The method of improving the dynamic range of analog-digital conversion of phase jitter signals in telecommunications systems

Abstract: The method of volume expansion of analog-todigital conversion path of jitter signals in telecommunication systems is suggested. As distinct from the current methods, the suggested one takes into account phase instability value of all analog-to-digital converter modules.

Cited by 8 publications

References 1 publication

Construction of mathematical models for the estimation of signal strength at the input to the 802.11 standard receiver in a 5 GHz band

Construction of mathematical models for the estimation of signal strength at the input to the 802.11 standard receiver in a 5 GHz band

Spectral-Covariation Method of Classification of Radio Signals

Phase irregularity: A conceptually simple and efficient approach to characterize electroencephalographic recordings from epilepsy patients

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