• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.6
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• pp.1080-1082
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• 2016

In a multi-hop CR (Cognitive Radio) network, each node find a path to destination node through several links. If links have the same frequency channel, there can be a serious interference among the links and it can reduce the network capacity. In multi-channel CR networks, each channel has different capacity according to the inter-link interference, and each channel has different traffic properties of primary users. In this paper, we propose channel scheduling scheme to minimize channel interferences and collision with primary users. Simulation results show the improvement of channel capacity and collision rate with primary users.

• 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.

• Korean Journal of Adult Nursing
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• v.19 no.1
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• pp.78-88
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• 2007

Purpose: The purpose of this study was to find out the degree of cognitive function among the elderly and to confirm its correlated factors. Methods: The subjects consisted of 392 elderly people over the age 65 who were living in Busan. Data were collected by the interview method, using a structured questionnaire and the K-MMSE scale. Results: The average points of the elderly's cognitive functions measured by K-MMSE were 23.76(${\pm}4.02$). With the cut-off point for cognitive impairment set as 24 points below using K-MMSE scale, 38.8% of the subjects have cognitive impairments. Among the variables related to cognitive functions, literacy showed the highest correlation with cognitive function(${\beta}=.330$, t=7.249, p<.001), followed in order by educational level, age, depression level, attendance of elderly's college, and religious activity. The total explanatory power of these variables is 36%. Conclusion: In order to prevent cognitive impairment among the elderly, elderly people have to maintain social relationships continuously, and expand the social network by participating in the related programs. Some efforts to prevent the occurrence of depression and to stimulate patients' brain activity need to be recommended.

• Korean Journal of Cognitive Science
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• v.7 no.4
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• pp.141-162
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• 1996

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.4
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• pp.629-631
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• 2012

In Cognitive Radio network, spectrum selection scheme is one of a important part to manage idle spectrums efficiently. However, in CR networks, they have to adopt time-varying channel availability to minimize the interference to primary users (PU), and be able to manage spectrum resources efficiently. In this paper, we proposed a modified PF scheduler which can be appropriate to schedule downlink CR users and channels, by considering the fairness and the throughput as well as the primary user characteristics of each channel.

• International Journal of Advanced Culture Technology
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• v.1 no.2
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• pp.18-23
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• 2013

In this paper, we consider the problem of designing optimal sensing time and the minimization of energy consumption in the Cognitive radio Network. Trade-off between throughput and the sensing time are observed, and the equations are derived for the optimal choice of design variables. In this paper, we also look at the optimization problem involving all the design parameters together. The advantages of the proposed scheme for the spectrum sensing and access process are shown through simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2561-2576
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• 2013

The ship ad-hoc network (SANET) extends the coverage of the high data-rate terrestrial communications to the ships with the reduced cost in maritime communications. Cognitive radio (CR) has the ability of sensing the radio environment and dynamically reconfiguring the operating parameters, which can make SANET utilize the spectrum efficiently. However, due to the dynamic topology nature and no central entity for data fusion in SANET, the interference brought into the primary network caused by the hidden primary user requires to be carefully managed by a sort of decentralized cooperative spectrum sensing schemes. In this paper, we propose a self-weighted decentralized cooperative spectrum sensing (SWDCSS) scheme to solve such a problem. The analytical and simulation results show that the proposed SWDCSS scheme is reliable to detect the primary user in SANET. As a result, secondary network can efficiently utilize the spectrum band of primary network with little interference to primary network. Referring the complementary receiver operating characteristic (ROC) curves, we observe that with a given false alarm probability, our proposed algorithm reduces the missing probability by 27% than the traditional embedded spectrally agile radio protocol for evacuation (ESCAPE) algorithm in the best condition.

• Korean Journal of Cognitive Science
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• v.4 no.1
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• pp.261-294
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• 1993

Most of expert systems,as a rule-based system,should be convenient to modify a rule and to insert a new rule, which is called modularity of rules. When we think correlated evidences in expert systems. conventional systems are too local to recognize the common origin of the information, and they would update the belief of the hypothesis as if it were supposed by independence soureces. In this paper to overcome such drawbacks we propose Fuzzy Belief Network which is based on the Beysian Network which provide the modulartiy between rules. To build Fuzzy Belief Network, we define nodes and links and propose algorithms for data fusion in individual node and for propagation belief value obtained as a result of data fusion.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1755-1777
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• 2022

The development of wireless communication technology has led to the underutilization of radio spectra. To address this limitation, an intelligent cognitive radio network was developed. Specific emitter identification (SEI) is a key technology in this network. However, in realistic non-cooperative scenarios, the system may detect signal classes beyond those in the training database, and only a few labeled signal samples are available for network training, both of which deteriorate identification performance. To overcome these challenges, a meta-learning-based open-set identification system is proposed for SEI. First, the received signals were pre-processed using bi-spectral analysis and a Radon transform to obtain signal representation vectors, which were then fed into an open-set SEI network. This network consisted of a deep feature extractor and an intrinsic feature memorizer that can detect signals of unknown classes and classify signals of different known classes. The training loss functions and the procedures of the open-set SEI network were then designed for parameter optimization. Considering the few-shot problems of open-set SEI, meta-training loss functions and meta-training procedures that require only a few labeled signal samples were further developed for open-set SEI network training. The experimental results demonstrate that this approach outperforms other state-of-the-art SEI methods in open-set scenarios. In addition, excellent open-set SEI performance was achieved using at least 50 training signal samples, and effective operation in low signal-to-noise ratio (SNR) environments was demonstrated.