• Journal of electromagnetic engineering and science
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• v.12 no.2
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• pp.148-154
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• 2012

In this paper, we propose an algorithm to conserve resources of the common control channel in a cognitive radio network by rejecting the redundant users using cooperative spectrum sensing. The proposed scheme is investigated under the paradigm of active spectrum sensing and a sequential detection technique. The algorithm is based on the J-divergence between the hypotheses of non primary user operation and the otherwise case. We select the most significant eigenvalues, which primarily affect the global statistical test. For the case where interference is from a secondary system transmission, a match filter is first employed to remove the degradation, and then the proposed algorithm is employed to remove the cooperative sensing nodes. Numerical results are provided and compared with conventional cases in order to validate the performance of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1392-1413
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• 2022

In order to meet the rapid development of the unmanned aerial vehicle (UAV) communication needs, cooperative spectrum sensing (CSS) helps to identify unused spectrum for the primary users (PU). However, multi-UAV mode (MUM) requires the large communication resource in a cognitive UAV network, resulting in a severe decline of spectrum efficiency (SE) and energy efficiency (EE) and increase of energy consumption (EC). On this account, we extend the traditional 2D spectrum space to 3D spectrum space for the UAV network scenario and enable UAVs to proceed with spectrum sensing behaviors in this paper, and propose a novel multi-slot mode (MSM), in which the sensing slot is divided into multiple mini-slots within a UAV. Then, the CSS process is developed into a composite hypothesis testing problem. Furthermore, to improve SE and EE and reduce EC, we use the sequential detection to make a global decision about the PU channel status. Based on this, we also consider a truncation scenario of the sequential detection under the sensing delay constraint, and further derive a closed-form performance expression, in terms of the CSS performance and cooperative efficiency. At last, the simulation results verify that the performance and cooperative efficiency of MSM outperforms that of the traditional MUM in a low EC.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2A
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• pp.124-131
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• 2009

Cognitive radio has been proposed to mitigate the spectrum scarcity problem by allowing the secondary users to access the under-utilized frequency bands and opportunistically transmit. Spectrum sensing, as a key technology in cognitive radio, is required to reliably detect the presence of primary users to avoid the harmful interference. However, it would be very hard to reliably detect the presence of primary users due to the channel fading, shadowing. In this paper, we proposed a distributed cooperative spectrum sensing scheme based on conventional DF (decode-and-forward) cooperative diversity protocol. We fist consider the cooperation between two secondary users to illustrate that cooperation among secondary users can obviously increase the detection performance. We then compare the performance of DF based scheme with another conventional AF (amplify-and-forward) protocol based scheme. And it is found that the proposed scheme based on DF has a better detection performance than the one based on AF. After that, we extend the number of cooperative secondary users, and demonstrate that increasing the cooperation number can significantly improve the detection performance.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.3
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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.

• Journal of Information Technology Services
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• v.15 no.1
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• pp.167-178
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• 2016

Spectrum sensing in cognitive radio (CR) has a great role in order to utilize idle spectrum opportunistically, since it is responsible for making available dynamic spectrum access efficiently. In this research area, collaboration among multiple cognitive radio users has been proposed for the betterment of detection reliability. Even though cooperation among them improves the spectrum sensing performance, some falsely reporting malicious users may degrade the performance rigorously. In this article, we have studied the detection and nullifying the harmful effects of such malicious users by applying some well known outlier detection methods based on Grubb's test, Boxplot method and Dixon's test in cooperative spectrum sensing. Initially, the performance of each technique is compared and found that Boxplot method outperforms both Grubb's and Dixon's test for the case where multiple malicious users are present. Secondly, a new algorithm based on reputation and weight is developed to identify malicious users and cancel out their negative impact in final decision making. Simulation results demonstrate that the proposed scheme effectively identifies the malicious users and suppress their harmful effects at the fusion center to decide whether the spectrum is idle.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.1043-1050
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• 2018

In this paper, we propose a reinforce learning based on cooperative sensing scheme to select optimal secondary users(SUs) to enhance the detection performance of spectrum sensing in Cognitive radio(CR) networks. The SU with high accuracy is identified based on the similarity between the global sensing result obtained through cooperative sensing and the local sensing result of the SU. A fusion center(FC) uses similarity of SUs as reward value for Q-learning to determine SUs which participate in cooperative sensing with accurate sensing results. The experimental results show that the proposed method improves the detection performance compared to conventional cooperative sensing schemes.

• 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

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1754-1769
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• 2013

For the purpose of enhancing the spectrum efficiency, cognitive radio (CR) technology has been recently proposed as a promising dynamic spectrum allocation paradigm. In CR, spectrum sensing is the key capability of secondary users in a cognitive radio network that aims for reducing the probability of harmful interference with primary users. However, the individual CRs might not be able to carry out reliable detection of the presence of a primary radio due to the impact of channel fading or shadowing. This paper studies the cooperative spectrum sensing scheme as means of optimizing the sensing performance in AWGN and Rayleigh channels. Results generated from simulation provide evidence of the impact of channel condition on the complementary receiver operating characteristic (ROC). Based on the results, it was found that with constant local SNRs at the secondary users, the probability of missed detection ($P_m$) of cooperative spectrum sensing in a cognitive radio network, calculated using a closed form expression, can be significantly minimized. Thus, the paper illustrates that improvement of the detection performance of the CR network can be achieved by establishing a centralized cooperation among neighboring cognitive radio users. Finally, verification of the validity of the fusion schemes utilized for combining the individual CR decisions is provided.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1A
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• pp.87-94
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• 2010

It is widely known that cooperative spectrum sensing in which secondary users scattered in some region collaborate to detect primary users can significantly reduce the performance degradation due to the fading phenomenon. Most of previous works on cooperative spectrum sensing are based on the assumption that the local spectrum sensing decisions of secondary users are statistically independent. However, there can be practically some statistical correlation between the local decisions of any two secondary users in close proximity, which is caused by shadowing effect. In order to evaluate the effect of this correlation on the performance of collaborative spectrum sensing, we assumed that, for the case that a primary user are active in the spectrum of interest, any two local decisions are statistically correlated to each other with some level of constant correlation and independent otherwise, and analyzed the achievable throughput with the degree of correlation varying. The results showed that, as the degree of correlation gets higher, the throughput increases for the case of the AND fusion rule and decreases for the OR fusion rule.