• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1532-1553
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• 2014

Radio spectrum is a precious resource and characterized by fixed allocation policy. However, a large portion of the allocated radio spectrum is underutilized. Conversely, the rapid development of ubiquitous wireless technologies increases the demand for radio spectrum. Cognitive Radio (CR) methodologies have been introduced as a promising approach in detecting the white spaces, allowing the unlicensed users to use the licensed spectrum thus realizing Dynamic Spectrum Access (DSA) in an effective manner. This paper proposes a generalized framework for DSA between the licensed (primary) and unlicensed (secondary) users based on Continuous Time Markov Chain (CTMC) model. We present a spectrum access scheme in the presence of sensing errors based on CTMC which aims to attain optimum spectrum access probabilities for the secondary users. The primary user occupancy is identified by spectrum sensing algorithms and the sensing errors are captured in the form of false alarm and mis-detection. Simulation results show the effectiveness of the proposed spectrum access scheme in terms of the throughput attained by the secondary users, throughput optimization using optimum access probabilities, probability of interference with increasing number of secondary users. The efficacy of the algorithm is analyzed for both imperfect spectrum sensing and perfect spectrum sensing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.980-998
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• 2023

In Low Earth Orbit (LEO) satellite networks, satellites operate fast and the inter-satellite link change period is short. In order to sense the spectrum state in LEO satellite networks in real-time, a space-based satellite network intelligent spectrum sensing algorithm based on artificial neural network (ANN) is proposed, while Geosynchronous Earth Orbit (GEO) satellites are introduced to make fast and effective judgments on the spectrum state of LEO satellites by using their stronger arithmetic power. Firstly, the visibility constraints between LEO satellites and GEO satellites are analyzed to derive the inter-satellite link building matrix and complete the inter-satellite link situational awareness. Secondly, an ANN-based energy detection (ANN-ED) algorithm is proposed based on the traditional energy detection algorithm and artificial neural network. The ANN module is used to determine the spectrum state and optimize the traditional energy detection algorithm. GEO satellites are used to fuse the information sensed by LEO satellites and then give the spectrum decision, thereby realizing the inter-satellite spectrum state sensing. Finally, the sensing quality is evaluated by the analysis of sensing delay and sensing energy consumption. The simulation results show that our proposed algorithm has lower complexity, the sensing delay and sensing energy consumption compared with the traditional energy detection method.

• Journal of information and communication convergence engineering
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• v.13 no.2
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• pp.74-80
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• 2015

In cognitive radios, spectrum sensing plays an important role in accurately detecting the presence or absence of a licensed user. However, the intervention of malicious users (MUs) degrades the performance of spectrum sensing. Such users manipulate the local results and send falsified data to the data fusion center; this process is called spectrum sensing data falsification (SSDF). Thus, MUs degrade the spectrum sensing performance and increase uncertainty issues. In this paper, we propose a method based on the Hausdorff distance and a similarity measure matrix to measure the difference between the normal user evidence and the malicious user evidence. In addition, we use the Dempster-Shafer theory to combine the sets of evidence from each normal user evidence. We compare the proposed method with the k-means and Jaccard distance methods for malicious user detection. Simulation results show that the proposed method is effective against an SSDF attack.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.2
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• pp.43-48
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• 2011

Cognitive radio is accepted as an effective and promising approach for resolving the spectrum scarcity problem by allowing secondary users to borrow unused spectrum from primary users. A method of identifying busy and empty spectrum at the given time and space, which is called spectrum sensing, constitutes an essential element of the cognitive radio. In this paper, we propose a receiver-centric spectrum sensing scheme which attempts to detect the primary receiver rather than the primary transmitter. It is shown that the proposed receiver-centric sensing approach results in more efficient spectrum utilization than the conventional transmitter-centric sensing.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8C
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• pp.713-719
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• 2010

Collaborative spectrum sensing has been found to be an effective means for detecting the activity of primary users in a fading environment. Most previous works on collaborative spectrum sensing are based on the assumption that the local spectrum sensing decisions of secondary users are statistically independent. However, it may not hold in some practical situations. In this paper, we consider a cognitive radio network where the local spectrum sensing decisions of secondary users are statistically correlated with the same level of correlation if they are next to each other in location and statistically independent, otherwise. Then, for the system, we analyzed the performance of the collaborative spectrum sensing with the AND and the OR fusion rules and found that the scheme with the AND fusion rule performs better than the one with OR fusion rule when the degree of correlation is significant.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.1998-2016
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• 2012

Reliable spectrum sensing algorithm is a fundamental component in cognitive radio. In this paper, a non-cooperative spectrum sensing algorithm which needs only one cognitive radio node named CORDIC (Coordinate Rotation Digital Computer) Jacobi based method is proposed. The algorithm computes the eigenvalues of the sampled covariance of received signal mainly by shift and additional operations, which is suitable for hardware implementation. Based the latest random matrix theory (RMT) about the distribution of the limiting maximum and minimum eigenvalue ratio, the relationship between the probability of false alarm and the decision threshold is derived. Simulations and discussions show the method is effective. Real captured digital television (DTV) signals and Universal Software Radio Peripheral (USRP) are also employed to evaluate the performance of the algorithm, which prove the proposed algorithm can be applied in practical spectrum sensing applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1042-1062
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• 2010

Cooperative spectrum sensing (CSS) is an effective technology for alleviating the unreliability of local spectrum sensing due to fading/shadowing effects. Unlike most existing solutions, this paper considers the use of CSS technology in decentralized networks where a fusion center is not available. In such a decentralized network, some attackers may sneak into the ranks of cooperative users. On the basis of recent advances in bio-inspired consensus algorithms, an attack-proof, decentralized CSS scheme is proposed in which all secondary users can maintain cooperative sensing by exchanging information locally instead of requiring centralized control or data fusion. Users no longer need any prior knowledge of the network. To counter three potential categories of spectrum sensing data falsification (SSDF) attacks, some anti-attack strategies are applied to the iterative process of information exchange. This enables most authentic users to exclude potentially malicious users from their neighborhood. As represented by simulation results, the proposed scheme can generally ensure that most authentic users reach a consensus within the given number of iterations, and it also demonstrates much better robustness against different SSDF attacks than several existing schemes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2A
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• pp.132-138
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• 2009

Cognitive radio is considered as a promising solution to scarce spectrum problem. The primary object of cognitive radio is to increase spectral efficiency, while causing limited interference to primary users who are using the spectrum. Hence, an essential part of cognitive radio systems is spectrum sensing which determines whether a particular spectrum is occupied or not by a primary user at a particular time. However, sensing decision of each individual secondary user alone may not be reliable enough due to shadowing and multipath fading of wireless channels. The so called hidden terminal problem makes the problem even worse, possibly yielding undesired interference to the primary users. Recently, cooperative spectrum sensing is emerging as a remedy to these problems of individual sensing. Cooperative sensing allows a group of secondary users to share local sensing information to extract a global decision with high fidelity. In this paper, we investigate a cooperative spectrum sensing algorithm based on hard decisions of local sensing outcomes. Specifically, we propose an effective scheme for combining local decisions by introducing weighting factors that reflect reliability of the corresponding secondary user. Through computer simulations, the performance of the proposed combining scheme is compared with that of the conventional scheme without weighting factors in various environments.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.6
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• pp.113-119
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• 2010

Wireless ad hoc network composed of low power devices has been operated in ISM bands. However, with the growing proliferation of wireless services, these bands are increasingly getting congested. In order to relieve the spectrum scarcity and inefficient spectrum utilization, ad ho cognitive radio was proposed. In this paper we propose the efficient spectrum sensing method to reduce power consumption and detect white space in ad hoc cognitive radio system. The wireless channel between a licensed user and CR systems is modeled as Gaussian channel, the distance between a licensed user and CR systems is assumed differently. Also, the wireless channel among CR systems is assumed as the perfect channel and the distance among CR systems is assumed close distance. CR systems sense the spectrum of the licensed user by using a energy detection method. From the simulation results, spectrum sensing performance of combining sensing result of CR systems with high received energy shows higher than combining sensing result of all CR systems and we can refer to the proposed sensing method in order to perform effective spectrum sensing with low power consumption.

• 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