• BMB Reports
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• v.44 no.10
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• pp.635-646
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• 2011

Due to its high external and low internal concentration the $Ca^{2+}$ ion is used ubiquitously as an intracellular signaling molecule, and a great many $Ca^{2+}$-sensing proteins have evolved to receive and propagate $Ca^{2+}$ signals. Among them are ion channel proteins, whose $Ca^{2+}$ sensitivity allows internal $Ca^{2+}$ to influence the electrical activity of cell membranes and to feedback-inhibit further $Ca^{2+}$ entry into the cytoplasm. In this review I will describe what is understood about the $Ca^{2+}$ sensing mechanisms of the three best studied classes of $Ca^{2+}$-sensitive ion channels: Large-conductance $Ca^{2+}$-activated $K^+$ channels, small-conductance $Ca^{2+}$-activated $K^+$ channels, and voltage-gated $Ca^{2+}$ channels. Great strides in mechanistic understanding have be made for each of these channel types in just the past few years.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.679-680
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• 2009

Radio jamming attack is the most effective and easiest Denial-of-Service (DOS) attack in wireless network. In this paper, we proposed a multi-channel MAC protocol to mitigate the jamming attacks by using cognitive radio. The Cognitive Radio (CR) technology supports real-time spectrum sensing and fast channel switching. By using CR technologies, the legitimate nodes can perform periodic spectrum sensing to identify jamming free channels and when the jamming attack is detected, it can switch to un-jammed channel with minimum channel switching delay. In our proposed protocol, these two CR technologies are exploited for thwarting the jamming attacks.

• Journal of information and communication convergence engineering
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• v.16 no.1
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• pp.23-30
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• 2018

In cognitive radio (CR), spectrum sensing is an essential function since secondary users (SUs) must determine whether the primary user (PU) is utilizing the channel or not, and furthermore, SUs opportunistically access the licensed channel when the PU is absent. In this paper, spectrum sensing is implemented by energy detection, and a software-defined radio testbed is built to evaluate sensing performance by energy detection in a real environment. In particular, the testbed was built based on the GNU's Not Unix (GNU) Radio software platform and Universal Software Radio Peripheral National Instruments 2900 devices. More specifically, a new block of energy detection is developed by using an out-of-tree module from GNU Radio. To successfully integrate CR into the cloud computing paradigm, we also implement cloud computing-based spectrum sensing by utilizing a cloud server with ThingSpeak, such that we can store, process, and share the sensing information more efficiently in a centralized way in the cloud server.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.4
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• pp.416-422
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• 2011

In this paper, we use hard decision method for cooperative spectrum sensing. Sensing performance adopting hard decision is lower than soft decision but system load is low and the process is relatively simple when the combining scheme is hard decision compared to soft decision. In order to improve sensing performance, we propose optimal hard decision method applying weight that is based on a probability of individual sensing. Unlike conventional hard decision, we try to improve sensing performance applying weight and show the performance of the proposed method from the simulation results and performance analysis. The signal of licensed user is OFDM signal and the wireless channel between a licensed user and CR systems is modeled as Gaussian channel.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.88-97
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• 2013

Most of the traditional spectrum sensing methods consider only the current detected data sets of Primary User (PU). However previous state of PU is a kind of conditional probability that strengthens the reliability of the detector. Therefore, in the cross entropy spectrum sensing method, relationship of the previous and current spectrum sensing is considered to detect PU signal more effectively. But these cross entropy spectrum sensing methods only consider the ideal system. In other words, PU always occupy the channel during the same period. However, PU can occupy the channel either for a longer or a shorter period than the ideal case in the real system. For this reason, the spectrum sensing performance can be varied. In this paper, we propose the method that can maintain the performance of spectrum sensing in the real system and we confirm the results with the help of simulation.

• Journal of IKEEE
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• v.26 no.3
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• pp.341-348
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• 2022

Wi-Fi Sensing, which uses Wi-Fi technology to sense the surrounding environments, has strong potentials in a variety of sensing applications. Recently several advanced deep learning-based solutions using CSI (Channel State Information) data have achieved high performance, but it is still difficult to use in practice without explicit data collection, which requires expensive adaptation efforts for model retraining. In this study, we propose a Channel State Information Automatic Labeling System (CALS) that automatically collects and labels training CSI data for deep learning-based Wi-Fi sensing systems. The proposed system allows the CSI data collection process to efficiently collect labeled CSI for labeling for supervised learning using computer vision technologies such as object detection algorithms. We built a prototype of CALS to demonstrate its efficiency and collected data to train deep learning models for detecting the presence of a person in an indoor environment, showing to achieve an accuracy of over 90% with the auto-labeled data sets generated by CALS.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.6-11
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• 2016

In this paper, we studied a spectrum sensing algorithm for the efficient use of available spectrum in RF energy harvesting system combined with backscatter communication. We first looked for white spaces and then, selected low fading channel among white spaces using spectrum sensing algorithm at a transmitter. The transmitter employing the algorithm alleviates signal interference and improves the received signal strength indication through signals transmitted by low fading channel. The proposed RF energy harvesting system combined with backscatter communication is used the transmitter employing the algorithm. As a result of computer simulations, we can find the performance improvements of RF energy harvesting, BER of backscatter communication, and the received signal strength per distance of backscatter tag.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2305-2315
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• 2015

Frequency resource value is growing more and more with the development of the wireless communication. With the advent of the current information society comes a serious shortage of frequency resource, as the amount of supply is far from meeting its demands. Thus, cognitive radio (CR) technique is receiving more attention as a way to make use of the temporarily unoccupied frequency resource. In this paper we propose a novel out-of-band spectrum sensing and dynamic channel access scheme for frequency hopping-based cognitive radio ad-hoc networks. At the beginning of each current channel hopping time, member nodes perform spectrum sensing for the next hopping channel. Based on the proposed collision free primary detection notification, member nodes can determine whether they should execute a hopping time extension procedure of the current channel or not. When the primary detected hopping channel is re-idled, the hopping pattern recovery procedure is performed. In this paper we evaluated the performance of the proposed dynamic sensing and hopping channel extension mechanism for the various wireless network conditions. As a result, we show that the proposed method can increase channel utilization and provide reliable channel management operation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.321-323
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• 2012

Cognitive radio has been recently proposed to dynamically access unused-spectrum. Since the spectrum availability for opportunistic access is determined by spectrum sensing, sensing is identified as one of the most crucial issues of cognitive radio networks. The PHY-layer sensing, as a part of spectrum sensing in cognitive radio, concerns the sensing mechanism to determine channel to be sensed and to access. One of the important issues in the PHY-layer sensing control is to find an available sensing period and trade-off between spectrum sensing and data transmission. In this paper, we show the relationship between spectrum sensing and data transmission according to the sensing period. We analyze and propose the new scheme to evaluate optimal sensing period.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.1
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• pp.25-30
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• 2017

Millimeter wave (mmWave) bands are expected to improve date rate of 5G systems due to the wide available bandwidth. While severe path loss in those bands has impeded the utilization, short wavelength enables a large number of antennas packed in a compact form, which can mitigate the path loss. However, estimating the channel with a conventional scheme requires a huge training overhead, hence an efficient estimation scheme operating with a small overhead needs to be developed. The sparsity of mmWave channels caused by the limited scatterers can be exploited to reduce the overhead by utilizing compressed sensing. In this paper, we introduce compressed sensing techniques for mmWave channel estimation. First, we formulate wideband channel estimation into a sparse recovery problem. We also analyze the characteristics of random measurement matrix constructed using quantized phase shifters in terms of mutual incoherence.