• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.980-998
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• 2023

In Low Earth Orbit (LEO) satellite networks, satellites operate fast and the inter-satellite link change period is short. In order to sense the spectrum state in LEO satellite networks in real-time, a space-based satellite network intelligent spectrum sensing algorithm based on artificial neural network (ANN) is proposed, while Geosynchronous Earth Orbit (GEO) satellites are introduced to make fast and effective judgments on the spectrum state of LEO satellites by using their stronger arithmetic power. Firstly, the visibility constraints between LEO satellites and GEO satellites are analyzed to derive the inter-satellite link building matrix and complete the inter-satellite link situational awareness. Secondly, an ANN-based energy detection (ANN-ED) algorithm is proposed based on the traditional energy detection algorithm and artificial neural network. The ANN module is used to determine the spectrum state and optimize the traditional energy detection algorithm. GEO satellites are used to fuse the information sensed by LEO satellites and then give the spectrum decision, thereby realizing the inter-satellite spectrum state sensing. Finally, the sensing quality is evaluated by the analysis of sensing delay and sensing energy consumption. The simulation results show that our proposed algorithm has lower complexity, the sensing delay and sensing energy consumption compared with the traditional energy detection method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.10
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• pp.832-842
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• 2013

Cognitive Radio has attracted intensive interests of the researchers, recently. The data rate always increases in the emerging technologies. The increased data rate poses mainly two challenges for spectrum sensing. One is that the state of primary user (PU) is fast and alternatively varying between "on/off" in a spectrum sensing window. The other is that the asynchronicity among the reports in a cooperative spectrum sensing setting becomes more apparent. Both of them would deteriorate the spectrum sensing performance. Thus, we propose an asynchronous cooperative spectrum sensing method to cope with these two challenges. A likelihood ratio test based spectrum sensing is developed for a single cooperator. The likelihood ratio is obtained in the setting of fast varying PU state. The likelihood ratio test is uniformly powerful according to the Neyman-pearson lemma. Furthermore, the asynchronicity among the cooperators are studied. Two sets of fusion weights are discussed for the asynchronous time among cooperators. One is designed based on the condition probability of the PU state variation and the other one is designed based on the queueing theory. The simulation results are provided with different fusion methods. The performance improvements are demonstrated.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.879-880
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• 2006

The subject of this paper is to recognize the stable state of EEG using wavelet transform and power spectrum analysis. An alpha wave, showed in stable state, is dominant wave for a human EEG and a beta wave displayed excited state. We decomposed EEG signal into an alpha wave and a beta wave in the process of wavelet transform. And we calculated each power spectrum of EEG signal, an alpha wave and a beta wave using Fast Fourier Transform. We recognized the stable state by making a comparison between power spectrum ratios respectively.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.3
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• pp.178-184
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• 2007

The EEG signal in general can be categorized as the Alpha wave, the Beta wave, the Theta wave, and the Delta wave. The alpha wave, showed in stable state, is the dominant wave for a human EEG and the beta wave displays the excited state. The subject of this paper was to recognize the stable state of EEG quantitatively using wavelet transform and power spectrum analysis. We decomposed EEG signal into the alpha wave and the beta wave in the process of wavelet transform, and calculated each power spectrum of EEG signal, using Fast Fourier Transform. And then we calculated the stable state quantitatively by stable state ratio, defined as the power spectrum of the alpha wave over that of the beta wave. The study showed that it took more than 10 minutes to reach the stable state from the normal activity in 69 % of the subjects, 5 -10 minutes in 9%, and less than 5 minutes in 16 %.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3029-3045
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• 2017

The main processes of a cognitive radio system include spectrum sensing, spectrum decision, spectrum sharing, and spectrum conversion. Experimental results show that these stages introduce a time delay that affects the spectrum sensing accuracy, reducing its efficiency. To reduce the time delay, the frequency spectrum prediction was proposed to alleviate the burden on the spectrum sensing. In this paper, the deep recurrent neural network (DRNN) was proposed to predict the spectrum of multiple time slots, since the existing methods only predict the spectrum of one time slot. The continuous state of a channel is divided into a many time slots, forming a time series of the channel state. Since there are more hidden layers in the DRNN than in the RNN, the DRNN has fading memory in its bottom layer as well as in the past input. In addition, the extended Kalman filter was used to train the DRNN, which overcomes the problem of slow convergence and the vanishing gradient of the gradient descent method. The spectrum prediction based on the DRNN was verified with a WiFi signal, and the error of the prediction was analyzed. The simulation results proved that the multiple slot spectrum prediction improved the spectrum efficiency and reduced the energy consumption of spectrum sensing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.549-554
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• 2006

The objective of this paper is to propose a system by means of which the utilization of radio frequency spectrum may be improved from the state of extreme inefficiency at the present time in Kazakhstan to a state of efficiency and equilibrium in the future. The main solutions to efficiently use radio frequency spectrum in Kazakhstan will be described in this paper. There are 'Spectrum Utilization, Spectrum Sharing and Reuse the Spectrum' in which the radio frequency can be propagated in wide range using smalt amount of spectrum, or broadcast several channels via one spectrum sharing. In order to embed these systems in practice it will be better to make modifications consider Government policy and geographical and social requirements.

• ETRI Journal
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• v.28 no.2
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• pp.250-252
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• 2006

In this letter, a discrete state, discrete time chaotic pseudo random number generator (CPRNG) is presented for stream ciphering of text, audio, or image data. The CPRNG is treated as a finite state machine, and its state is modulated according to the input bit sequence of the signal to be encrypted. The modulated state sequence obtained can be transmitted as a spread spectrum or encrypted data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3751-3774
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• 2014

With the rapid development of wireless communication, the confliction between the scarce frequency resources and the low spectral efficiency caused by the stationary spectrum sharing strategies seriously restricts the evolution of the future mobile communication. For this purpose, cognitive radio (CR) emerges as one of the most promising inventions which can overcome the spectrum shortage. As the key technology and main objective of CR, spectrum sharing can make full use of the limited spectrum, alleviate the scarcity of frequency resources and improve the system utilities, playing thereby an important role in improving the system performance of cognitive radio networks (CRNs). In this survey, the spectrum sharing in CRNs is discussed in terms of the sharing process, mainstream sharing technologies and spectrum sharing models. In particular, comparisons of different spectrum sharing strategies are concluded, as well as that of different spectrum sensing schemes in sharing procedure. Moreover, some application examples of the spectrum sharing in CRNs, such as smart grid, public safety, cellular network and medical body area networks are also introduced. In addition, our previous related works are presented and the open research issues in the field of spectrum sharing are stated as well.

• Journal of Photoscience
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• v.10 no.1
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• pp.149-155
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• 2003

The absorption, fluorescence and fluorescence-excitation spectra of concentrated toluene solutions of selected para substituted trans-stilbene derivatives provide strong evidence for aggregation. A red-shifted fluorescence spectrum peaking at 420 nm gains in intensity as the stilbene concentration is increased. The excitation spectrum of this new emission is well to the red of the normal stilbene absorption spectrum, consistent with the appearance of a red shifted shoulder in the UV spectrum. Formation of a fluorescent ground state dimer (or higher aggregate) is proposed to account for these observations. The presence of polar substituents is crucial to the formation of this ground state complex.

• Journal of information and communication convergence engineering
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• v.4 no.2
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• pp.53-57
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• 2006

The objective of this paper is to propose a system by means of which the utilization of radio frequency. spectrum may be improved from the state of extreme inefficiency at the present time in Kazakhstan to a state of efficiency and equilibrium in the future.