• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.6
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• pp.1133-1146
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• 2011

Cognitive radio (CR) is considered one of the most promising next-generation communication systems; it has the ability to sense and make use of vacant channels that are unused by licensed users. Reliable detection of the licensed users' signals is an essential element for a CR network. Cooperative spectrum sensing (CSS) is able to offer better sensing performance as compared to individual sensing. The presence of malicious users who falsify sensing data can severely degrade the sensing performance of the CSS scheme. In this paper, we investigate a secure CSS scheme, based on the Kullback-Leibler Divergence (KL-divergence) theory, in order to identify malicious users and mitigate their harmful effect on the sensing performance of CSS in a CR network. The simulation results prove the effectiveness of the proposed scheme.

• Journal of electromagnetic engineering and science
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• v.11 no.4
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• pp.250-256
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• 2011

This paper applies a compressed algorithm to improve the spectrum sensing performance of cognitive radio technology. At the fusion center, the recovery error in the analog to information converter (AIC) when reconstructing the transmit signal from the received time-discrete signal causes degradation of the detection performance. Therefore, we propose a subspace pursuit (SP) algorithm to reduce the recovery error and thereby enhance the detection performance. In this study, we employ a wide-band, low SNR, distributed compressed sensing regime to analyze and evaluate the proposed approach. Simulations are provided to demonstrate the performance of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2755-2773
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• 2015

Cooperative spectrum sensing increases the detection performance in a cognitive radio network, based on the number of sensing nodes. However, as the number of sensing nodes increases, the reporting overhead linearly increases. This paper proposes two kinds of cooperative spectrum sensing with limited reporting in a centralized cognitive radio network, a soft combination with threshold-based reporting (SC-TR) and a soft combination with contention-based reporting (SC-CR). In the proposed SC-TR scheme, each sensing node reports its sensing result to the fusion center through its own reporting channel only if the observed energy value is higher than a decision threshold. In the proposed SC-CR scheme, sensing nodes compete to report their sensing results via shared reporting channels. The simulation results show that the proposed schemes significantly reduce the reporting overhead without sacrificing the detection performance too much.

• Journal of Internet Computing and Services
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• v.12 no.1
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• pp.1-10
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• 2011

The spectrum sensing is one of the fundamental functions to realize the cognitive radios. One of problems in the spectrum sensing is that the performance of spectrum sensing can be degraded due to fading and shadowing. In order to overcome the problem, cooperative spectrum sensing method is proposed, which uses a distributed detection model and can increase sensing performance. However, the performance of cooperative spectrum sensing can be still affected by the interference factors such as obstacle and malicious user. Especially, most of cooperative spectrum sensing methods only considered the stationary primary user. In the ubiquitous environment, however the mobile primary users should be considered. In order to overcome the aforementioned problem, in this paper we propose a robust spectrum detection method based on localization where we estimate the location of the mobile primary user, and then based on the location and transmission range of primary user we detect interference users if there are, and then the local sensing reporting from detected interference users are excluded in the decision fusion process. Through simulation, it is shown that the sensing performance of the proposed scheme is more accurate than that of conventional other schemes

• Journal of Communications and Networks
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• v.16 no.2
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• pp.162-171
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• 2014

Spectrum sensing is a key technical challenge for cognitive radio (CR). It is well known that multicycle cyclostationarity (MC) detection is a powerful method for spectrum sensing. However, a conventional MC detector is difficult to implement because of its high computational complexity. This paper considers reducing computational complexity by simplifying the test statistic of a conventional MC detector. On the basis of this simplification process, an improved MC detector is proposed. Compared with the conventional detector, the proposed detector has low-computational complexity and high-accuracy sensing performance. Subsequently, the sensing performance is further investigated for the cases of Rayleigh, Nakagami-m, Rician, and Rayleigh fading and lognormal shadowing channels. Furthermore, square-law combining (SLC) is introduced to improve the detection capability in fading and shadowing environments. The corresponding closed-form expressions of average detection probability are derived for each case by the moment generation function (MGF) and contour integral approaches. Finally, illustrative and analytical results show the efficiency and reliability of the proposed detector and the improvement in sensing performance by SLC in multipath fading and lognormal shadowing environments.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.1
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• pp.89-93
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• 2009

In this paper, we investigated effect of sensing time on the performance of enhanced spectrum sensing method, which is the energy detector with multiples of verification using time delay, under Suzuki channel. We assumed that SNR is 1dB, $P_{FA}=0.1$ and various mobile speed such as 3, 60, 110 km/h. The performance is investigated by simulation and compared to that of conventional energy detector.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2497-2517
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• 2020

For compressed sensing (CS) applications, it is significant to construct deterministic measurement matrices with good practical features, including good sensing performance, low memory cost, low computational complexity and easy hardware implementation. In this paper, a deterministic construction method of bipolar measurement matrices is presented based on binary sequence family (BSF). This method is of interest to be applied for sparse signal restore and image block CS. Coherence is an important tool to describe and compare the performance of various sensing matrices. Lower coherence implies higher reconstruction accuracy. The coherence of proposed measurement matrices is analyzed and derived to be smaller than the corresponding Gaussian and Bernoulli random matrices. Simulation experiments show that the proposed matrices outperform the corresponding Gaussian, Bernoulli, binary and chaotic bipolar matrices in reconstruction accuracy. Meanwhile, the proposed matrices can reduce the reconstruction time compared with their Gaussian counterpart. Moreover, the proposed matrices are very efficient for sensing performance, memory, complexity and hardware realization, which is beneficial to practical CS.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.1
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• pp.287-304
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• 2012

Spectrum sensing is an important functionality for cognitive users to look for spectrum holes before taking transmission in dynamic spectrum access model. Unlike previous works that assume perfect knowledge of the SNR of the signal received from the primary user, in this paper we consider a realistic case where the SNR of the primary user's signal is unknown to both fusion center and cognitive radio terminals. A Kalman filter based adaptive Takagi and Sugeno's fuzzy system is designed to make the global spectrum sensing decision based on the observed energies from cognitive users. With the capacity of adapting system parameters, the fusion center can make a global sensing decision reliably without any requirement of channel state information, prior knowledge and prior probabilities of the primary user's signal. Numerical results prove that the sensing performance of the proposed scheme outperforms the performance of the equal gain combination based scheme, and matches the performance of the optimal soft combination scheme.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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• pp.278-282
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• 1995

We developed a part of storke sensing cylinder using magnetic sensor and estimated is performance. In this paper, for the performance estimation of stroke sensing cylinder. We consist of hydrallic system using solenoid valve with ON/OFF motion. In order to the control of solenoid valve for the position control of cylinder rod, PWM (Pulse Width Modulation) method which modulates time pulse width in proportion to error was used. A performance of cylinder rod with magnetic scales was evaluated by its hydraulic system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.284-287
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• 2001

This paper presents the robust control simulation of a composite beam using self-sensing actuators(SSA). The self-sensing actuator is a new concept for intelligent material, where a single piezoelectric element simultaneously functions as both a sensor and an actuator. In a practical implementation of the self-sensing actuator an electrical bridge circuit is used to measure strain. The circuit could provide significant information about strain in the element if it were well-balanced. Our aim is design a robust controller which guarantees that the performance of a self-sensing actuator is robust against perturbation of the bridge balance and to confirm the advantages of this technique. Simulation results show that the self-sensing actuator driven by the designed controller exhibits excellent performance in suppressing the vibration of a composite beam.