• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1313-1336
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• 2020

Cognitive radio (CR) is regarded as an effective approach to avoid the inefficient use of spectrum. However, CRNs have more special security problems compared with the traditional wireless communication systems due to its open and dynamic characteristics. Primary user emulation attack (PUEA) is a common method which can hinder secondary users (SUs) from accessing the spectrum by transmitting signals who has the similar characteristics of the primary users' (PUs) signals, and then the SUs' quality of service (QoS) cannot be guaranteed. To handle this issue, we first design a multiple-phase energy detection scheme based on the cooperation of multiple SUs to detect the PUEA more precisely. Second, a joint SUs scheduling and power allocation scheme is proposed to maximize the weighted effective capacity of multiple SUs with a constraint of the average interference to the PU. The simulation results show that the proposed method can effectively improve the effective capacity of the secondary users compared with the traditional overlay scheme which cannot be aware of the existence of PUEA. Also the good delay QoS guarantee for the secondary users is provided.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2037-2051
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• 2012

Cognitive radio (CR) is envisioned as a promising paradigm of exploiting intelligence for enhancing efficiency of underutilized spectrum bands. In CR, the main concern is to reliably sense the presence of primary users (PUs) to attain protection against harmful interference caused by potential spectrum access of secondary users (SUs). In this paper, evolutionary algorithms, namely, particle swarm optimization (PSO) and genetic algorithm (GA) are proposed to minimize the total sensing decision error at the common soft data fusion (SDF) centre of a structurally-centralized cognitive radio network (CRN). Using these techniques, evolutionary operations are invoked to optimize the weighting coefficients applied on the sensing measurement components received from multiple cooperative SUs. The proposed methods are compared with each other as well as with other conventional deterministic algorithms such as maximal ratio combining (MRC) and equal gain combining (EGC). Computer simulations confirm the superiority of the PSO-based scheme over the GA-based and other conventional MRC and EGC schemes in terms of detection performance. In addition, the PSO-based scheme also shows promising convergence performance as compared to the GA-based scheme. This makes PSO an adequate solution to meet real-time requirements.

• ETRI Journal
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• v.37 no.3
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• pp.491-501
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• 2015

Spectrum sensing is an elementary function in cognitive radio designed to monitor the existence of a primary user (PU). To achieve a high rate of detection, most techniques rely on knowledge of prior spectrum patterns, with a trade-off between high computational complexity and long sensing time. On the other hand, blind techniques ignore pattern matching processes to reduce processing time, but their accuracy degrades greatly at low signal-to-noise ratios. To achieve both a high rate of detection and short sensing time, we propose fast spectrum sensing with coordinate system (FSC) - a novel technique that decomposes a spectrum with high complexity into a new coordinate system of salient features and that uses these features in its PU detection process. Not only is the space of a buffer that is used to store information about a PU reduced, but also the sensing process is fast. The performance of FSC is evaluated according to its accuracy and sensing time against six other well-known conventional techniques through a wireless microphone signal based on the IEEE 802.22 standard. FSC gives the best performance overall.

• ETRI Journal
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• v.37 no.3
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• pp.471-479
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• 2015

Traditional designs of cognitive radio (CR) focus on maximizing system throughput. In this paper, we study the joint overlay and underlay power allocation problem for orthogonal frequency-division multiple access-based CR. Instead of maximizing system throughput, we aim to maximize system energy efficiency (EE), measured by a "bit per Joule" metric, while maintaining the minimal rate requirement of a given CR system, under the total power constraint of a secondary user and interference constraints of primary users. The formulated energy-efficient power allocation (EEPA) problem is nonconvex; to make it solvable, we first transform the original problem into a convex optimization problem via fractional programming, and then the Lagrange dual decomposition method is used to solve the equivalent convex optimization problem. Finally, an optimal EEPA allocation scheme is proposed. Numerical results show that the proposed method can achieve better EE performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.10B
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• pp.621-629
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• 2007

In cognitive radio (CR) network, the channels are generally classified into either the unavailable channels that are occupied by incumbent users or the available channels that are not occupied. The conventional channel classification scheme may result in poor utilization of spectrum holes since it does not take the spatial relationship between CR node and incumbent users into consideration. In this paper, we propose an efficient channel management scheme for the centralized CR network to maximize the spectrum holes by overcoming the shortcomings of conventional scheme. In addition, we mathematically analyze the effectiveness of proposed scheme. Based on the proposed channel management scheme, we also propose the rendezvous algorithm, which can establish the control channels between base station and CR node under the dynamically changing spectrum environment.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.1
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• pp.140-142
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• 2013

Cognitive radio (CR) has been recently proposed to dynamically access unused-spectrum. Since the spectrum availability for opportunistic access is determined by spectrum sensing, sensing control is identified as one of the most crucial issues of cognitive radio networks. Out-of-band sensing to find an available channels to sense. Sensing is also required in case of spectrum hand-off. Sensing process needs to be done very fast in order to enhance the quality of service (QoS) of the CR nodes, and transmission not to be cut for longer time. During the sensing, the PU(primary user) detection probability condition should be satisfied. We adopt a channel prediction method to find target channels. Proposed prediction method combines chaotic global method and chaotic local method for channel idle probability prediction. Global method focus on channel history information length and order number of prediction model. Local method focus on local prediction trend. Through making simulation, Proposed method can find an available channel with very high probability, total sensing time is minimized, detection probability of PU's are satisfied.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.9
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• pp.751-764
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• 2013

In cognitive radio ad-hoc networks, common control channel overload and packet collisions are occured due to indiscriminate broadcasting of control packets. So that the path reliability is reduced and control channel is easily saturated. In this paper, we propose a new routing algorithm considering the probability of appearance of primary user and channel status of neighbor nodes. When the source node needs to transmit a data packet to the destination, it performs route discovery process by exchanging control messages using a control channel in ADOV CR Ad-hoc networks. If any intermediate node doesn't have common data channel with previous node to transmit data, it doesn't rebroadcast control packet. And if it has common data channels with previous node, each node determines channel contribution factor with the number of common channels. Based on the channel contribution factor, each node performs different back-off broadcasting. In addition, each node controls control packet flooding by applying to proposed advanced mode using such as number of available channels and channel stability. With the proposed method, the number of control packets to find the data transmission path and the probability of collision among control packets can be decreased. While the path reliability can be increased. Through simulation, we show that our proposed algorithm reduces packet collisions in comparison with the traditional algorithm.

• Journal of KIISE
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• v.43 no.12
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• pp.1412-1419
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• 2016

In cognitive radio sensor networks (CRSNs), secondary users (SUs) can occupy licensed bands opportunistically without causing interferences to primary users (PUs). SUs perform spectrum sensing to detect the presence of PUs. Sensing time is a critical parameter for spectrum sensing that can yield a tradeoff between sensing performance and secondary throughput. In this study, we investigate new approaches for spectrum sensing by exploring the tradeoff from a) spectrum sensing for PU detection (SSPD) and b) spectrum sensing for secondary throughput (SSST). In the proposed scheme, the first sensing result of the current frame determines the dynamic performance of the second spectrum sensing. Energy constraint in CRSNs leads to maximized network energy efficiency via optimization of sensing time. Simulation results show that the proposed scheme of SSPD and SSST improves network performance in terms of energy efficiency and secondary throughput, respectively.

• Journal of Advanced Navigation Technology
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• v.20 no.5
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• pp.440-445
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• 2016

There is a scheme where secondary users (SU) use predicted spectrum holes for primary users (PU) not to utilize for efficient utilization of the limited spectrum resources in cognitive radio networks. In this paper, we propose an adaptive call admission control framework that minimizes spectrum hopping call dropped probability (SHDP) for satisfying SU quality of service (QoS). The scheme is based on a call admission control (CAC), bandwidth prediction and adaptive bandwidth assignment. The prediction model predicts not only the number of spectrum holes, but requested bandwidth of SU spectrum hopping call, and then the CAC minimizes SHDP via an adaptive bandwidth assignment in resources not being enough for reservation. We bring Wiener prediction model to predict the resources. Simulations are conducted to compare the performance of proposed scheme with an existing, and show its ability of minimizing the SHDP.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.81-88
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• 2018

Spectrum sensing, the key technology of the cognitive radio networks, is used by a secondary user to determine the frequency state of a primary user. The energy detection in the spectrum sensing determines the presence or absence of a primary user according to the intensity of the allocated channel signal. Since this technique simply uses the strength of the signal for spectrum sensing, it is difficult to detect the signal of a primary user in the low SNR band. In this paper, we propose a way to combine spectrum sensing and support vector machine using wavelet packet decomposition to overcome performance degradation in low SNR band. In our proposed scheme, the sensing signals were extracted by wavelet packet decomposition and then used as training data and test data for support vector machine. The simulation results of the proposed scheme are compared with the energy detection using the AUC of the ROC curve and the accuracy according to the SNR band. With simulation results, we demonstrate that the proposed scheme show better determining performance than one of energy detection in the low SNR band.