• 한국항행학회논문지
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• 제12권5호
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• pp.429-436
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• 2008

본 논문에서는 무선인지통신망에서 스펙트럼 센싱을 위한 협업 센싱을 하는 경우에 센싱 시간 및 협업 센싱 단말 수의 최적값들을 결정하는 방식에 대해서 다룬다. 협업 스펙트럼 센싱에서는 전송 중인 CU (Cognitive User) 외에 휴지중인 다른 CU들이 활성화되어 센싱에 참여함으로써 센싱 시간을 줄일 수 있다. 이로 인한 전송 CU의 전송률 이득과 CU들의 센싱으로 인한 에너지 소모간의 관계를 모두 고려하는 혼합 정수 계획법 문제를 풀어서 최적값들을 구할 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권3호
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• pp.1319-1335
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• 2017

This paper proposes an opportunistic reporting-based sensing-reporting-throughput optimization scheme that maximizes the spectral efficiency of secondary users (SUs) in cooperative cognitive radio networks with a soft combining rule. The performance of cooperative spectrum sensing depends on the sensing time, the reporting time of transmitting sensing results, and the fusion scheme. While longer sensing time and reporting time improve the sensing performance, this shortens the allowable data transmission time, which in turn degrades the spectral efficiency of SUs. The proposed scheme adopts an opportunistic reporting scheme to restrain the reporting overhead and it jointly controls the sensing-reporting overhead in order to increase the spectral efficiency of SUs. We show that there is a trade-off between the spectral efficiency of SUs and the overheads of cooperative spectrum sensing. The numerical results demonstrate that the proposed scheme significantly outperforms the conventional sensing-throughput optimization schemes when there are many SUs. Moreover, the numerical results show that the sensing-reporting time should be jointly optimized in order to maximize the spectral efficiency of SUs.

• 한국ITS학회:학술대회논문집
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• 한국ITS학회 2010년도 춘계학술대회
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• pp.48-52
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• 2010

• International Journal of Internet, Broadcasting and Communication
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• 제10권3호
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• pp.59-64
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• 2018

A cooperative spectrum sensing has been proposed to improve the sensing performance in cognitive radio (CR) network. However, cooperative sensing causes additional overhead for reporting the result of local sensing to the fusion center. In this paper, we propose a technique to reduce the overhead of data transmission of cooperative sensing for applying the quantum data fusion technique in cognitive radio networks by omitting the lowest quantized in the local sensed results. If a CR node senses the lowest quantized level, it will not send its local sensing data in the corresponding sensing period. The fusion center can implcitly know that a spectific CR node sensed lowest level if there is no report from that CR node. The goal of proposed sensing policy is to reduce the overhead of quantized data fusion scheme for cooperative sensing. Also, our scheme can be adapted to all quantized data fusion schemes because it only deal with the form of the quantized data report. The experimental results show that the proposed scheme improves performance in terms of reporting overhead.

• 한국전자통신학회논문지
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• 제13권5호
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• pp.1043-1050
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• 2018

본 논문은 인지 무선(CR, Cognitive Radio) 네트워크에서 우선 사용자(Primary User)의 존재 유무를 2차 사용자(Secondary User)가 결정하기 위하여 협력 센싱을 사용하는 환경에서 스펙트럼 센싱의 감지 성능을 높이기 위해 강화 학습(Reinforce learning) 기반으로 최적의 인지 무선 사용자 선택하는 협력 센싱 방안을 제안한다. 협력 센싱을 통해 파악한 전역 센싱 결과와 인지 무선 사용자의 센싱 결과 간의 유사도에 따라 정확도가 높은 사용자를 파악한다. 이 정확도를 강화학습의 보상으로 사용하여 협력 센싱을 수행할수록 전역 결정과 일치하는 센싱 정보를 전송하는 사용자를 선택할 수 있다. 실험 결과 제안한 기법이 기존 협력 센싱 대비 향상된 스펙트럼 감지 성능을 보임을 확인할 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권1호
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• pp.58-73
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• 2014

As is well known, cooperative sensing can significantly improve the sensing accuracy as compared to local sensing in cognitive radio networks (CRNs). However, a large number of cooperative secondary users (SUs) reporting their local detection results to the fusion center (FC) would cause much overhead, such as sensing delay and energy consumption. In this paper, we propose a fast cooperative sensing scheme, called double threshold fusion (DTF), to reduce the sensing overhead while satisfying a given sensing accuracy requirement. In DTF, FC respectively compares the number of successfully received local decisions and that of failed receptions with two different thresholds to make a final decision in each reporting sub-slot during a sensing process, where cooperative SUs sequentially report their local decisions in a selective fashion to reduce the reporting overhead. By jointly considering sequential detection and selective reporting techniques in DTF, the overhead of cooperative sensing can be significantly reduced. Besides, we study the performance optimization problems with different objectives for DTF and develop three optimum fusion rules accordingly. Simulation results reveal that DTF shows evident performance gains over an existing scheme.

• Journal of information and communication convergence engineering
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• 제13권4호
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• pp.221-227
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• 2015

Spectrum sensing plays an essential role in a cognitive radio network, which enables opportunistic access to an underutilized licensed spectrum. In conventional cooperative spectrum sensing (CSS), all cognitive users (CUs) in the network spend the same amount of time on spectrum sensing and waste time in remaining silent when other CUs report their sensing results to the fusion center. This problem is solved by the superposition cooperative spectrum sensing (SPCSS) scheme, where the sensing time of a CU is extended to the reporting time of the other CUs. Subsequently, SPCSS assigns the CUs different sensing times and thus affects both the sensing performance and the throughput of the system. In this paper, we propose an algorithm to determine the optimal sensing time of each CU for SPCSS that maximizes the achieved system throughput. The simulation results prove that the proposed scheme can significantly improve the throughput of the cognitive radio network compared with the conventional CSS.

• Journal of Information Processing Systems
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• 제12권2호
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권2호
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• pp.355-370
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• 2014

Cooperative spectrum sensing has been considered as a promising approach to improve the sensing performance in distributed cognitive radio networks. However, there may exist some selfish secondary users (SUs) who are unwilling to cooperate. The presence of selfish SUs could cause catastrophic damage to the performance of cooperative spectrum sensing. Following the social perspective, we propose a Social Tie-based Incentive Scheme (STIS) to deal with the selfish problem for cooperative spectrum sensing in distributed cognitive radio networks. This scheme inspires SUs to contribute sensing information for the SUs who have social tie but not others, and such willingness varies with the strength of social tie value. The evaluation of each SU's social tie derives from its contribution for others. Finally, simulation results validate the effectiveness of the proposed scheme.

• 한국통신학회논문지
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• 제40권2호
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• pp.253-263
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• 2015

최근 다수의 후 순위 사용자(Secondary User)가 각각의 검출 결과를 융합 센터(Fusion Center)에 보고하여 대역 검출의 성능을 향상시키기 위한 협력 대역 검출 기법이 이루어지고 있다. 또한 선 순위 사용자(Primary User)에게 할당된 주파수 대역을 융합 센터가 공유하는 인지 무선(Cognitive Radio)기술이 개발되고 있다. 이 논문에서는 분산 협력 대역 검출 환경에서 후 순위 사용자의 검출 정보가 융합 센터로 보고되는 채널의 오류 확률을 고려한 기존 분산 협력 대역 검출 기법의 성능 저하를 보완하는 새로운 분산 협력 대역 검출 기법을 제안하였다. 또한 분산 협력 대역 검출 기법의 오류 확률을 최소화 하는 검출 문턱값의 최적화 방법을 수식의 유도를 통해 제안하였다. 최적의 검출 문턱값은 분산 협력 대역 검출의 성능을 최대화 하는 것을 확인하였다.