• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.391-395
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• 2011

Cognitive radio (CR) technique is a useful tool for improving spectrum utilization by detecting and using the vacant frequency bands while avoiding interference to the primary user. The sensing performance in a CR network can be improved by allowing some CR users to perform cooperative spectrum sensing. In this paper, we propose a new sensing algorithm that utilizes an adaptive energy threshold for cooperative spectrum sensing in which a changeable energy threshold is adopted by the CR users for improving local sensing performance. Through the proposed scheme, the reliability of global decision can be enhanced mainly due to the improvement in local sensing performance.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.604-615
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• 2019

Single-user spectrum sensing is susceptible to multipath effects, shadow effects, hidden terminals and other unfavorable factors, leading to misjudgment of perceived results. In order to increase the detection accuracy and reduce spectrum sensing cost, we propose an adaptive cooperative sensing strategy based on an estimated signal-to-noise ratio (SNR). Which can adaptive select different sensing strategy during the local sensing phase. When the estimated SNR is higher than the selection threshold, adaptive double threshold energy detector (ED) is implemented, otherwise cyclostationary feature detector is performed. Due to the fact that only a better sensing strategy is implemented in a period, the detection accuracy is improved under the condition of low SNR with low complexity. The local sensing node transmits the perceived results through the control channel to the fusion center (FC), and uses voting rule to make the hard decision. Thus the transmission bandwidth is effectively saved. Simulation results show that the proposed scheme can effectively improve the system detection probability, shorten the average sensing time, and has better robustness without largely increasing the costs of sensing system.

• 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.10 no.1
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• pp.58-78
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• 2016

Compressed sensing (CS) possesses the potential benefits for spectrum sensing of wideband signal in cognitive radio. The sparsity of signal in frequency domain denotes the number of occupied channels for spectrum sensing. This paper presents a scheme of adaptively adjusting the number of compressed measurements to reduce the unnecessary computational complexity when priori information about the sparsity of signal cannot be acquired. Firstly, a method of sparsity estimation is introduced because the sparsity of signal is not available in some cognitive radio environments, and the relationship between the amount of used data and estimation accuracy is discussed. Then the SNR of the compressed signal is derived in the closed form. Based on the SNR of the compressed signal and estimated sparsity, an adaptive algorithm of adjusting the number of compressed measurements is proposed. Finally, some simulations are performed, and the results illustrate that the simulations agree with theoretical analysis, which prove the effectiveness of the proposed adaptive adjusting of compressed measurements.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.984-996
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• 2014

In this paper, optimal sensing time allocation for adaptive multiband spectrum sensing-transmission procedure is investigated. The sensing procedure consists of an exploration phase and a detection phase. We first formulate an optimization problem to maximize the throughput by designing not only the overall sensing time, but also the sensing time for every stage in the exploration and detection phases, while keeping the miss detection probability for each channel under a pre-defined threshold. Then, we transform the initial non-convex optimization problem into a convex bilevel optimization problem to make it mathematically tractable. Simulation results show that the optimized sensing time setting in this paper can provide a significant performance gain over the previous studies.

• Journal of Satellite, Information and Communications
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• v.8 no.1
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• pp.61-65
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• 2013

In this paper, we propose system model to solve conventional threshold problem of using fixed false alarm for energy spectrum sensing. Spectrum sensing reliability is ensured when Secondary user have high SNR. Thus, it is not reasonable using fixed optional false alarm without considering CR user's SNR. So, we propose adaptive threshold method. adaptive threshold is decided by controling FA according to CR user's SNR.

• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.141-145
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• 2017

Spectrum sensing is a critical functionality of Cognitive Radio(CR) systems and the CR systems can be applied to RF energy harvesting systems to improve an energy harvesting rate. There are number of spectrum sensing techniques. One of techniques is energy detection. Energy detection is the simplest detection method and is the most commonly used. But, energy detection has a hidden terminal problem in real wireless communication, because of secondary user (SU) can be affected by frequency fading and shadowing. Cooperative spectrum sensing can solve this problem using spatial diversity of SUs. But it has a problem of increasing data by processing multiple secondary. So, we propose the system model using adaptive spectrum sensing algorithm and system model is simulated. This algorithm chooses sensing method between single energy sensing and cooperative energy according to the received signal's Signal to Noise Ratio (SNR) from Primary User (PU). The simulation result shows that adaptive spectrum sensing has an efficiency and improvement in CR systems.

• Journal of information and communication convergence engineering
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• v.9 no.3
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• pp.251-255
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• 2011

In this paper, we investigate an adaptive cognitive radio (CR) scheme where a sensing duration and a detection threshold for spectrum sensing are adaptively determined according to the channel condition in a fading channel. We optimize the sensing duration and detection threshold of a secondary user to maximize the performance of the secondary user guaranteeing a primary user's secure communication. In addition, we analyze the effect of channel fading on the optimization of the sensing duration and detection threshold. Our numerical results show that the performance of the adaptive CR scheme can be drastically improved if a secondary user can take the advantage of channel information between primary and secondary users.

• Annual Conference of KIPS
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• 2019.05a
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• pp.82-85
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• 2019

An adaptive power control scheme is proposed for the cognitive relay networks with joint overlay and underlay spectrum sharing model. The transmit power of the secondary user is adjusted adaptively according to the spectrum sensing results and the interference channel condition. The outage probability of the secondary user is compared by Monte - Carlo simulations between the fixed power control scheme and pure overlay or underlay spectrum sharing schemes. The results show that, by employing the adaptive power control strategy, the interference probability of the secondary user to the primary user is decreased by 70 % ~ 80 % under the same outage probability. Also, the outage probability of the secondary user is reduced by 1 ~ 2 orders of magnitude under the same interference probability. Thus, the performance of the spectrum sharing is improved effectively.