• Earthquakes and Structures
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• v.12 no.2
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• pp.177-189
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• 2017

For energy-based seismic design, a simplified normalized cumulative hysteretic energy spectrum proposed for obtaining hysteretic energy as energy demand is the main objective in this paper. The dimensionless parameter, ${\beta}_{Eh}$, is presented to express hysteretic energy indirectly. The ${\beta}_{Eh}$ spectrum is constructed directly through subtracting the hysteretic energy of single degree-of-freedom (SDOF) system energy equation. The simplified ${\beta}_{Eh}$ spectral formulation as well as pseudo-acceleration spectrum of modern seismic provisions is developed based on the regression analysis of the large number of seismic responses of SDOF system subjected to earthquake excitations, which considers the influence of earthquake event, soil type, damping ratio, and ductility factor. The relationship between PGV and PGA is established according to the statistical analysis relied on a total of 422 ground motion records. The combination of ${\beta}_{Eh}$ spectrum and PGV/PGA equation allows determining the cumulative hysteretic energy as a main aseismic design indicator.

• Journal of Information Processing Systems
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• v.12 no.2
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• pp.295-309
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• 2016

Spectrum sensing is an essential function that enables cognitive radio technology to explore spectral holes and resourcefully access them without any harmful interference to the licenses user. Spectrum sensing done by a single node is highly affected by fading and shadowing. Thus, to overcome this, cooperative spectrum sensing was introduced. Currently, the advancements in multiple antennas have given a new dimension to cognitive radio research. In this paper, we propose a multiple energy detector for cooperative spectrum sensing schemes based on the evidence theory. Also, we propose a reporting mechanism for multiple energy detectors. With our proposed system, we show that a multiple energy detector using a cooperative spectrum sensing scheme based on evidence theory increases the reliability of the system, which ultimately increases the spectrum sensing and reduces the reporting time. Also in simulation results, we show the probability of error for the proposed system. Our simulation results show that our proposed system outperforms the conventional energy detector system.

• Journal of Communications and Networks
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• v.14 no.2
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• pp.188-194
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• 2012

Cognitive networks (CNs) are capable of enabling dynamic spectrum allocation, and thus constitute a promising technology for future wireless communication. Whereas, the implementation of CN will lead to the requirement of an increased energy-arrival rate, which is a significant parameter in energy harvesting design of a cognitive user (CU) device. A well-designed spectrum-sensing scheme will lower the energy-arrival rate that is required and enable CNs to self-sustain, which will also help alleviate global warming. In this paper, spectrum sensing in a multi-user cognitive ad hoc network with a wide-band spectrum is considered. Based on the prospective spectrum sensing, we classify CN operation into two modes: Distributed and centralized. In a distributed network, each CU conducts spectrum sensing for its own data transmission, while in a centralized network, there is only one cognitive cluster header which performs spectrum sensing and broadcasts its sensing results to other CUs. Thus, a wide-band spectrum that is divided into multiple sub-channels can be sensed simultaneously in a distributed manner or sequentially in a centralized manner. We consider the energy consumption for spectrum sensing only of an analog-to-digital convertor (ADC). By formulating energy consumption for spectrum sensing in terms of the sub-channel sampling rate and whole-band sensing time, the sampling rate and whole-band sensing time that are optimal for minimizing the total energy consumption within sensing reliability constraints are obtained. A power dissipation model of an ADC, which plays an important role in formulating the energy efficiency problem, is presented. Using AD9051 as an ADC example, our numerical results show that the optimal sensing parameters will achieve a reduction in the energy-arrival rate of up to 97.7% and 50% in a distributed and a centralized network, respectively, when comparing the optimal and worst-case energy consumption for given system settings.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.1
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• pp.34-39
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• 2014

In cognitive radios, secondary users can use the spectrum exclusively allocated to a primary wireless system if the secondary users detect the spectrum in idle states. Because the secondary users can utilize the idle state of the spectrum, the utilization rate of the spectrum can be improved. The idle states can be detected by using secondary users' sensing schemes. However, the wireless channel environment where secondary users perform the spectrum sensing is not very friendly to secondary users because the signal-to-noise ratio of the received primary signal is very low. Hence, cooperative sensing scheme where more than one secondary user take part in the spectrum sensing is generally used in cognitive radios. In this paper, we investigate the cooperative sensing performance for machine-to-machine communication devices operated by batteries with limited energy. In general, the energy consumed for the spectrum sensing increases as the length of the sensing period and the number of cooperative sensing nodes. Accordingly, even though the total amount of the consumed energy is the same, an energy allocation methodology how to distribute the energy to the sensing period and sensing nodes can achieve the optimum sensing performance, which is numerically analyzed.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.6
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• pp.357-366
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• 2013

Spectrum sensing, as a fundamental functionality of Cognitive Radio (CR), enables Secondary Users (SUs) to monitor the spectrum and detect spectrum holes that could be used. Recently, the security issues of Cognitive Radio Networks (CRNs) have attracted increasing research attention. As one of the attacks against CRNs, a Primary User Emulation (PUE) attack compromises the spectrum sensing of CR, where an attacker monopolizes the spectrum holes by impersonating the Primary User (PU) to prevent SUs from accessing the idle frequency bands. Energy detection is often used to sense the spectrum in CRNs, but the presence of PUE attack has not been considered. This study examined the effect of PUE attack on the performance of energy detection-based spectrum sensing technique. In the proposed protocol, the stationary helper nodes (HNs) are deployed in multiple stages and distributed over the coverage area of the PUs to deliver spectrum status information to the next stage of HNs and to SUs. On the other hand, the first stage of HNs is also responsible for inferring the existence of the PU based on the energy detection technique. In addition, this system provides the detection threshold under the constraints imposed on the probabilities of a miss detection and false alarm.

• The Journal of the Acoustical Society of Korea
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• v.9 no.3
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• pp.56-61
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• 1990

A New theoretical energy spectrum model for underwater explosive sound is introduced in order to calculate the precise spectral energy levels. This model is obtained by Fourier analysis of Gaussian formula which accurately represents the pressure wave generated from Underwater explosions. In case that explosive energy is very low. The spectrum levels which are obtained from the new theoretical model are in good agreement with the experimental spectrum levels, while the Weston model using impulse formula cannot interpret the experimental results.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.73-76
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• 2015

In this paper, we propose energy harvesting apply to spectrum sensing. In this case, we can be spectrum sensing without consume energy. Algorithms of sensing and harvesting are determine active or idle of primary network, Compares with the threshold energy and the amount of energy that is harvested by energy harvesting scheme. If the secondary network want to send a message while the primary network is active, secondary users will change frequency to use the spectrum. Further, if the secondary network has not message, it will continues harvest energy. Therefore, spectrum sensing applied the energy harvesting method, energy of secondary network is remove waste and charge energy. So, efficiency and utilization of cognitive network can be increase.

• 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.

• Nuclear Engineering and Technology
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• v.55 no.1
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• pp.190-200
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• 2023

As the field of application of in-situ gamma spectroscopy is diversified, proficiency is required for consistent and accurate analysis. In this study, a program was developed to virtually create gamma energy spectra of artificial nuclides, which are difficult to obtain through actual measurements, for training. The virtual spectrum was created by synthesizing the spectra of the background radiation obtained through actual measurement and the theoretical spectra of the artificial radionuclides obtained by a Monte Carlo simulation. Since the theoretical spectrum can only be obtained for a given geometrical structure, representative major geometries for in-situ measurement (ground surface, concrete wall, radioactive waste drum) and the detectors (HPGe, NaI(Tl), LaBr₃(Ce)) were predetermined. Generated virtual spectra were verified in terms of validity and harmonization by gamma spectrometry and energy calibration. As a result, it was confirmed that the energy calibration results including the peaks of the measured spectrum and the peaks of the theoretical spectrum showed differences of less than 1 keV from the actual energies, and that the calculated radioactivity showed a difference within 20% from the actual inputted radioactivity. The verified data were assembled into a database and a program that can generate a virtual spectrum of desired condition was developed.

• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.141-145
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• 2017

Spectrum sensing is a critical functionality of Cognitive Radio(CR) systems and the CR systems can be applied to RF energy harvesting systems to improve an energy harvesting rate. There are number of spectrum sensing techniques. One of techniques is energy detection. Energy detection is the simplest detection method and is the most commonly used. But, energy detection has a hidden terminal problem in real wireless communication, because of secondary user (SU) can be affected by frequency fading and shadowing. Cooperative spectrum sensing can solve this problem using spatial diversity of SUs. But it has a problem of increasing data by processing multiple secondary. So, we propose the system model using adaptive spectrum sensing algorithm and system model is simulated. This algorithm chooses sensing method between single energy sensing and cooperative energy according to the received signal's Signal to Noise Ratio (SNR) from Primary User (PU). The simulation result shows that adaptive spectrum sensing has an efficiency and improvement in CR systems.