• Journal of Satellite, Information and Communications
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• v.9 no.3
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• pp.91-97
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• 2014

In this paper, we propose weighted detection probability with distance between primary user and secondary users by using cooperative spectrum sensing based on energy detection. And we analysis and simulate the result. We suggest different distance between primary user and secondary users and the wireless channel between primary user and secondary users is modeled as Gaussian channel. From the simulation results of the cooperative spectrum sensing with weighted method make coverage bigger compared with non-weight, and We show higher sensing efficiency when we put weight detection probability than before method.

• Journal of Internet Computing and Services
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• v.13 no.1
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• pp.1-6
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• 2012

In the paper, an information divergence called Kullback-Leiber divergence, which measures the average of the logarithmic difference between two probability density functions, is utilized to derive a novel method for spectrum sensing in cognitive radio systems. In the proposed sensing method, we test whether the observed samples are drawn from the noise distribution by using Kullback-Leiber divergence. It is shown by numerical results that under the same conditions, the proposed Kullback-Leiber divergence-based spectrum sensing always outperforms the energy detection based spectrum sensing significantly, especially in low SNR regime and in fading circumstance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.11
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• pp.937-942
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• 2012

In cognitive radio (CR) systems, the secondary user (SU) performs the spectrum sensing to determine the presence of the primary user (PU) on the PU's frequency band. In practical cases, the PU would arrive and depart randomly in the sensing duration of the SU, which is referred to as the high traffic circumstance. In this paper, we propose a cyclostationarity-based spectrum sensing scheme for CR systems in high traffic circumstances. From numerical results, it is confirmed that the proposed scheme outperforms both the energy detector proposed for high traffic circumstances and the conventional cyclostationarity-based spectrum sensing scheme.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.45-49
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• 2015

In this paper, we proposed not specturm sensing but also save energy without consume energy of secondary network that spectrum sensing of cognitive applied energy harvesting scheme. Algorithms of sensing and harvesting is determine active or idle of primary network, compares the amount of energy that is harvested by energy harvesting scheme with the threshold. If secondary network to send a message and primary network is active, by changing frequency to use the spectrum. Further, if secondary network have no message, continues energy harvest. Therefore, spectrum sensing applied energy harvesting scheme, energy of secondary network is remove waste and charge energy, efficiency and utilization of cognitive network can be increase.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.564-571
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• 2009

In this paper, we propose out-of -band collaborative spectrum sensing scheme in the cognitive radio (CR) base station operated by the multiple frequency channels. Also this paper presents the signal detection results for ATSC digital TV signal as an incumbent signal and derives signal detection probability and false alarm probability for the out-of-band collaborative spectrum sensing scheme in frequency selective Rayleigh fading channel. Numerical results demonstrate that the sensing performance is improved by the out-of-band collaborative spectrum sensing in the case that the incumbent signal powers measured by the CR terminals of the multiple frequency channels are almost similar.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.5
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• pp.71-76
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• 2013

This paper considers an approach of secondary user selection method in cooperative spectrum sensing, which two users with the best SNR in sensing channel and in reporting channel, respectively, are selected to cooperate with each other in the spectrum sensing. The sensing results reported by two users are then combined to detect PU signal operation. A comparison between this proposed method with conventional selection technique in which only the user having the best sensing channel SNR is selected shows that the proposed method outperforms. We make an assumption that sensing channels experience identical, independent distributed (i.i.d) Rayleigh fading and the reporting channels are invariant and non-identical. Simulation results are derived for demonstration.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.3
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• pp.85-94
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• 2011

Spectrum sensing is one of the most important technologies in cognitive radio. Although many studies have considered energy detection technique as the spectrum sensing technique, noise variance in practical systems is difficult to estimate accurately. Thus, in the real system, the probability of false alarm will not be maintained constant. In this paper, with considering that the cognitive radio does not know the primary user's signal, we propose a new spectrum sensing scheme which can operate without the information of noise variance. Through simulations, we show that the proposed scheme can detect spectrum with the condition of unknown noise information and have robustness for the change of noise variance.

• Journal of information and communication convergence engineering
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• v.13 no.4
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• pp.241-247
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• 2015

Cognitive radio has been attracting increased attention as an effective approach to improving spectrum efficiency. One component of cognitive radio, spectrum sensing, has an important relationship with the performance of cognitive radio. In this paper, after a summary and analysis of the existing spectrum-sensing algorithms, we report that the existing eigenvalue-based semi-blind detection algorithm and blind detection algorithm have not made full use of the eigenvalues of the received signals. Applying multi-antenna systems to cognitive users, we design a variety of spectrum-sensing algorithms based on the joint distribution of the eigenvalues of the received signal. Simulation results validate that the proposed algorithms in this paper are able to detect whether the signal of the primary user exists or not with high probability of detection in an environment with a low signal-to-noise ratio. Compared with traditional algorithms, the new algorithms have the advantages of high detection performance and strong robustness

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.4A
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• pp.458-466
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• 2008

Spectrum sensing is the key challenge in implementing cognitive radio system, which enables unlicensed users to identify "white holes" in the spectrum allocated to primary users and utilize them efficiently. Recent studies have proposed three major sensing methods for WRAN systems, including matched filter, energy and feature detector. However, there are some drawbacks along with them. In this paper, we propose an enhanced energy detector that extends the ability of conventional one, which can differentiate the primary users from each other as well as the noise with different maximum-to-mean power ratio. Furthermore, a novel structure of cognitive radio detector employing the proposed algorithm is also analyzed to implement spectrum sensing. The simulation result shows that our proposed scheme performs well in the individual sensing environment and can satisfy the requirement with high detection probability.

• Journal of electromagnetic engineering and science
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• v.11 no.4
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• pp.250-256
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• 2011

This paper applies a compressed algorithm to improve the spectrum sensing performance of cognitive radio technology. At the fusion center, the recovery error in the analog to information converter (AIC) when reconstructing the transmit signal from the received time-discrete signal causes degradation of the detection performance. Therefore, we propose a subspace pursuit (SP) algorithm to reduce the recovery error and thereby enhance the detection performance. In this study, we employ a wide-band, low SNR, distributed compressed sensing regime to analyze and evaluate the proposed approach. Simulations are provided to demonstrate the performance of the proposed algorithm.