• ETRI Journal
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• v.41 no.2
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• pp.176-183
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• 2019

Spectrum sensing plays an important role in spectrum sharing. Energy detection is generally used because it does not require a priori knowledge of primary user (PU) signals; however, it is sensitive to noise uncertainty. An order statistics (OS) detector provides inherent protection against nonhomogeneous background signals. However, no analysis has been conducted yet to apply OS detection to spectrum sensing in a wireless channel to solve noise uncertainty. In this paper, we propose a robust spectrum sensing scheme based on generalized order statistics (GOS) and analyze the exact false alarm and detection probabilities under noise uncertainty. From the equation of the exact false alarm probability, the threshold value is calculated to maintain a constant false alarm rate. The detection probability is obtained from the calculated threshold under noise uncertainty. As a fusion rule for cooperative spectrum sensing, we adopt an OR rule, that is, a 1-out-of-N rule, and we call the proposed scheme GOS-OR. The analytical results show that the GOS-OR scheme can achieve optimum performance and maintain the desired false alarm rates if the coefficients of the GOS-OR detector can be correctly selected.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.6
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• pp.357-366
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• 2013

Spectrum sensing, as a fundamental functionality of Cognitive Radio (CR), enables Secondary Users (SUs) to monitor the spectrum and detect spectrum holes that could be used. Recently, the security issues of Cognitive Radio Networks (CRNs) have attracted increasing research attention. As one of the attacks against CRNs, a Primary User Emulation (PUE) attack compromises the spectrum sensing of CR, where an attacker monopolizes the spectrum holes by impersonating the Primary User (PU) to prevent SUs from accessing the idle frequency bands. Energy detection is often used to sense the spectrum in CRNs, but the presence of PUE attack has not been considered. This study examined the effect of PUE attack on the performance of energy detection-based spectrum sensing technique. In the proposed protocol, the stationary helper nodes (HNs) are deployed in multiple stages and distributed over the coverage area of the PUs to deliver spectrum status information to the next stage of HNs and to SUs. On the other hand, the first stage of HNs is also responsible for inferring the existence of the PU based on the energy detection technique. In addition, this system provides the detection threshold under the constraints imposed on the probabilities of a miss detection and false alarm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.39-46
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• 2013

Cooperative spectrum sensing can improve sensing reliability, compared with single node spectrum sensing. In addition, Eigenvalue-based spectrum sensing has also drawn a great attention due to its performance improvement over the energy detection method in which the more smoothing factor, the better performance is achieved. However, the more smoothing factor in Eignevalue-based spectrum sensing requires the more sensing time. Furthermore, more reporting time in cooperative sensing will be required as the number of nodes increases. Subsequently, we in this paper propose an Eigenvalue and superposition-based spectrum sensing where the reporting time is utilized so as to increase the number of smoothing factors for autocorrelation calculation. Simulation result demonstrates that the proposed scheme has better detection probability in both local as well as global detection while requiring less sensing time as compared with conventional Eigenvalue-based detection scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4387-4404
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• 2015

The energy-efficient design of sensing-based spectrum sharing of a multi-input and multi-output (MIMO) cognitive radio (CR) system with imperfect multiple antenna spectrum sensing is investigated in this study. Optimal resource allocation strategies, including sensing time and power allocation schemes, are studied to maximize the energy efficiency (EE) of the secondary base station under the transmit power and interference power constraints. EE problem is formulated as a nonlinear stochastic fractional programming of a nonconvex optimal problem. The EE problem is transformed into its equivalent nonlinear parametric programming and solved by one-dimension search algorithm. To reduce searching complexity, the search range was founded by demonstration. Furthermore, simulation results confirms that an optimal sensing time exists to maximize EE, and shows that EE is affected by the spectrum detection factors and corresponding constraints.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3638-3654
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• 2014

Cognitive Radio (CR) users need to sense the environment or channel at regular time interval for sharing the spectrum band of the primary users (PUs). Once find the spectrum idle, CR users start their transmission through it. Even while transmitting, they need to continue the sensing process so that they can leave the spectrum immediately whenever find a PU wanting to use the band. Therefore, detecting PUs is one of the main functions of cognitive radio before transmission and higher the detection probability ensures better protection to the primary users. However, it is not possible to attain a high detection probability (or a low miss detection probability) and low false alarm probability simultaneously as there is a tradeoff between false alarm probability ($P_{fa}$) and the probability of detection ($P_d$). In this paper, the author has provided a comprehensive study on different sensing techniques and discussed their advantages and disadvantages. Moreover, it is expected that, with this article, readers can have a through understanding of sensing techniques in CR and the current research trends in this area.

• Journal of electromagnetic engineering and science
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• v.12 no.3
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• pp.203-209
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• 2012

In order to improve sensing performance when the noise variance is not known, this paper considers a so-called blind spectrum sensing technique that is based on eigenvalue models. In this paper, we employed the spiked population models in order to identify the miss detection probability. At first, we try to estimate the unknown noise variance based on the blind measurements at a secondary location. We then investigate the performance of detection, in terms of both theoretical and empirical aspects, after applying this estimated noise variance result. In addition, we study the effects of the number of SUs and the number of samples on the spectrum sensing performance.

• Journal of Communications and Networks
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• v.11 no.2
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• pp.115-121
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• 2009

In cognitive radio (CR) systems, cognitive users can use the frequency bands when the primary users are not present. Hence, reliable detection of available spectrum is foundation of cognitive radio technology. To ensure unimpaired operation of primary users, cooperative spectrum sensing is needed. To reduce the network overhead of cooperative spectrum sensing, a novel cooperative spectrum sensing algorithm based on credibility is proposed. In particular, the close-form expressions for probability of detection and false-alarm are derived for the novel algorithm, and expression for the average overhead used for cooperation is given. The thresholds design method for the algorithm is also discussed. The conclusion is proved by computer simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.5
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• pp.461-474
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• 2009

The cognitive radio (CR) technique is a useful tool for improving spectrum utilization by detecting and using the vacant spectrum bands in which cooperative spectrum sensing is a key element, while avoiding interfering with the primary user. In this paper, we propose a novel cluster-based cooperative spectrum sensing scheme in cognitive radio with two solutions for the purpose of improving in sensing performance. First, for the cluster header, we use the double adaptive energy thresholds and a multi-bit quantization with different quantization interval for improving the cluster performance. Second, in the common receiver, the weighed HALF-voting rule will be applied to achieve a better combination of all cluster decisions into a global decision.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.7C
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• pp.672-679
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• 2006

Cognitive radio, which is designed to dynamically adapt its transmission to the environments, is believed to be one of the fundamental techniques for future spectrum utilization. As the first step of cognitive radio, spectrum sensing is treated as the most important technique, through which cognition is well explained. In this paper, we propose a spectral correlation based detection method for spectrum sensing. An unlicensed secondary user system operating in TV broadcast bands is taken as an example. Based on the cyclostationarity of communication signals, spectral correlation function is used to minimize the effect of random noise and interference. Energy measurement and peak detection based criteria are proposed. Simulation results show that the proposed detection method outperforms the energy detection and is more suitable for spectrum sensing in cognitive radios.

• Journal of information and communication convergence engineering
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• v.12 no.2
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• pp.97-103
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• 2014

In spectrum sensing, there is a tradeoff between the probability of missed detection and the probability of a false alarm according to the value of the sensing threshold. Therefore, it is important to determine the sensing threshold suitable to the environment of cognitive radio networks. In this study, we consider a cognitive radio-based ad hoc network where secondary users directly communicate by using the same frequency band as the primary system and control their transmit power on the basis of the distance between them. First, we investigate a condition in which the primary and the secondary users can share the same frequency band without harmful interference from each other, and then, propose an algorithm that controls the sensing threshold dynamically on the basis of the transmit power of the secondary user. The analysis and simulation results show that the proposed sensing threshold control algorithm has low probabilities of both missed detection and a false alarm and thus, enables optimized spectrum sharing between the primary and the secondary systems.