• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3638-3654
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• 2014

Cognitive Radio (CR) users need to sense the environment or channel at regular time interval for sharing the spectrum band of the primary users (PUs). Once find the spectrum idle, CR users start their transmission through it. Even while transmitting, they need to continue the sensing process so that they can leave the spectrum immediately whenever find a PU wanting to use the band. Therefore, detecting PUs is one of the main functions of cognitive radio before transmission and higher the detection probability ensures better protection to the primary users. However, it is not possible to attain a high detection probability (or a low miss detection probability) and low false alarm probability simultaneously as there is a tradeoff between false alarm probability ($P_{fa}$) and the probability of detection ($P_d$). In this paper, the author has provided a comprehensive study on different sensing techniques and discussed their advantages and disadvantages. Moreover, it is expected that, with this article, readers can have a through understanding of sensing techniques in CR and the current research trends in this area.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2213-2231
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• 2013

Compressed sensing is a novel technology used in the field of wireless communication and sensor networks for channel estimation, signal detection, data gathering, network monitoring, and other applications. It plays a significant role in highly secure, real-time, well organized, and cost-effective data communication in smart-grid (SG) systems, which consist of multi-tier network standards that make it challenging to synchronize in power management communication. In this paper, we present a multi-layer communication model for SG systems and propose compressed-sensing based data transmission at every layer of the SG system to improve data transmission performance. Our approach is to utilize the compressed-sensing procedure at every layer in a controlled manner. Simulation results demonstrate that the proposed monitoring devices need less transmission power than conventional systems. Additionally, secure, reliable, and real-time data transmission is possible with the compressed-sensing technique.

• 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 Power Electronics
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• v.17 no.5
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• pp.416-422
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• 2012

This paper proposes a low power-loss current measurement using a resistor and bypass switch. Conventional current sensing method using a resistor has a disadvantage of power loss which degrades the efficiency of the entire systems. On the other hand, proposed measurement technique operating with bypass-switch connected in parallel with sensing resistor can reduce power loss significantly the current sensor. The propose measurement works for discrete-time sampling of current sensing. Even while the analog-digital conversion does not occur at the controller, the sensing voltage across the sensor still causes ohmic conduction loss without information delivery. Hence, the bypass switch bypasses the sensing current with a small amount of power loss. In this paper, a 90[W] prototype hardware has been implemented for photovoltaic MPPT experimental verification of the proposed low power-loss current measurement technique. From the results, it can be seen that PV power observation is successfully done with the proposed method.

• Journal of Biomedical Engineering Research
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• v.31 no.6
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• pp.464-471
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• 2010

Compressed sensing can be used to reduce scan time or to enhance spatial resolution in MRI. It is now recognized that compressed sensing works well in reconstructing magnitude images if the sampling mask and the sparsifying transform are well chosen. Phase images also play important roles in MRI particularly in chemical shift imaging and magnetic resonance electrical impedance tomography (MREIT). We reconstruct MRI phase images using the compressed sensing technique. Through computer simulation and real MRI experiments, we reconstructed phase images using the compressed sensing technique and we compared them with the ones reconstructed by conventional Fourier reconstruction technique. As compared to conventional Fourier reconstruction with the same number of phase encoding steps, compressed sensing shows better performance in terms of mean squared phase error and edge preservation. We expect compressed sensing can be used to reduce the scan time or to enhance spatial resolution of MREIT.

• Transactions on Electrical and Electronic Materials
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• v.14 no.5
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• pp.235-241
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• 2013

A low power CMOS control circuit is applied in an integrated DC-DC buck converter. The integrated converter is composed of a feedback control circuit and power block with 0.35 ${\mu}m$ CMOS process. A current-sensing circuit is integrated with the sense-FET method in the control circuit. In the current-sensing circuit, a current-mirror is used for a voltage follower in order to reduce power consumption with a smaller chip-size. The N-channel MOS acts as a switching device in the current-sensing circuit where the sensing FET is in parallel with the power MOSFET. The amplifier and comparator are designed to obtain a high gain and a fast transient time. The converter offers well-controlled output and accurately sensed inductor current. Simulation work shows that the current-sensing circuit is operated with an accuracy of higher than 90% and the transient time of the error amplifier is controlled within $75{\mu}sec$. The sensing current is in the range of a few hundred ${\mu}A$ at a frequency of 0.6~2 MHz and an input voltage of 3~5 V. The output voltage is obtained as expected with the ripple ratio within 1%.

• Journal of Computing Science and Engineering
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• v.8 no.1
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• pp.17-24
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• 2014

In this paper, we propose a new implementation of a failure detector. The implementation uses a dual model of heartbeat and interaction. First, the heartbeat model is adopted to shorten the detection time, if the detection process does not receive the heartbeat message in the expected time. The interaction model is then used to check the process further. The expected time is calculated using the exponential smoothing method. Exponential smoothing can be used to estimate the next arrival time not only in the random data, but also in the data of linear trends. It is proven that the new detector in the paper can eventually be a perfect detector.

• Proceedings of the Safety Management and Science Conference
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• 2009.11a
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• pp.461-470
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• 2009

A railroad has a benefit of the mass transportation of a passenger and cargo, but just a time of accident could cause a huge loss of a human life and property. Especially, a typhoon and a localized torrential downpour usually happened in summer season have caused average 38.29 times of the missing roadbed which support the railroad in recent 7 years. If a train would pass on this railroad which the roadbed was missed, there could be a huge accident and many people will die. But, the security issue is not satisfied because the method of sensing the missing roadbed is depending solely on the naked eye inspection by a person in charge. So, in this study, I would like to suggest the missing roadbed real-time sensing and train operation system to reduce the possibility of the railroad accident by controlling the operation of train when the missing roadbed condition would be sensed in the real-time system.

• Journal of electromagnetic engineering and science
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• v.12 no.1
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• pp.1-7
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• 2012

In this paper, we investigated the throughput of a cognitive radio network where two primary frequency channels (PCs) are sensed and opportunistically accessed by N secondary users. The sharing sensing member (SSM) protocol is introduced to sense both PCs simultaneously. According to the SSM protocol, N SUs (Secondary User) are divided into two groups, which allows for the simultaneous sensing of two PCs. With a frame structure, after determining whether the PCs are idle or active during a sensing slot, the SUs may use the remaining time to transmit their own data. The throughput of the network is formulated as a convex optimization problem. We then evaluated an iterative algorithm to allocate the optimal sensing time, fusion rule and the number of members in each group. The computer simulation and numerical results show that the proposed optimal allocation improves the throughput of the SU under a misdetection constraint to protect the PCs. If not, its initial date of receipt shall be nullified.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.550-565
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• 2018

Cognitive radio technology is still the key technology of future mobile communication systems. Previous studies have focused on improving spectrum utilization and less energy consumption. In this paper, we propose an Overhead Reduced Scheme (ORS) for green cooperative spectrum sensing. Compared to traditional cooperative sensing scheme, ORS scheme divides the sensing time into three time slots and selects the best multi-mode user to report decisions. In consideration of reporting channel deviation, we derive closed-form expressions for detection probability and false alarm probability of ORS scheme based on Rayleigh fading channel. Simulation results show that ORS scheme can improve the perception accuracy while reducing the perceived delay and energy consumption in the process of perception, so as to realize the green communication.