• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.3A
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• pp.287-295
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• 2011

Cognitive radio (CR) features opportunistic access to spectrum when licensed users (LU) are not operating. To avoid interference to LU, cognitive users (CU) need to perform spectrum sensing. Because of local shadowing, fading, or limited sensing capability, it is suggested that multiple CUs cooperate to detect LU. In cooperative spectrum sensing, CUs should exchange their sensing data with minimum bandwidth and delay. In this paper, we introduce a novel method to efficiently report sensing data to the central node in an infrastructured OFDM-based CR network. All CUs simultaneously report their sensing data over unique and orthogonal signals on locally available subcarriers. By detecting the signals, the central node can determine subcarrier availability for each CU. Implementation challenges are identified and then their solutions are suggested. The proposed method is evaluated through simulation on a realistic channel model. The results show that the proposed method is feasible and efficient.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.2
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• pp.184-201
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• 2013

In this paper, we study the problem of designing the power and number of cooperative node (CN) in the cooperation phase to maximize the average throughput for secondary user (SU), under the constraint of the total cooperation and transmission power. We first investigate the scheme of cooperative spectrum sensing without a separated control channel. Then, we prove that there indeed exist an optimal CN power when the number of CNs is fixed and an optimal CN number when CN power is fixed. The case without the constraints of the power and number of CN is also studied. Finally, numerical results demonstrate the characteristics and existences of optimal CN power and number. Meanwhile, Monte Carlo simulation results match to the theoretical results well.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5A
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• pp.429-435
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• 2009

Cooperative spectrum sensing allows secondary users of a cognitive radio(CR) network to collaborate to determine whether a primary user occupies the spectrum of interest or not. It usually performs spectrum sensing by combining the individual decisions of each second user into a final one and the k-out-of-n fusion rule is a general approach for decision fusion. This rule declares that the spectrum is occupied only when the decisions from more than k-1 secondary users indicate the presence of a primary user. In this paper, we analyze a cooperative spectrum sensing scheme with the fusion rule under the constraint that its detection probability is maintained to be no less than a given level and its numerical results for the case of a CR network with 10 secondary users.

• Journal of Communications and Networks
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• v.11 no.2
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• pp.122-133
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• 2009

As wireless spectrum resources become more scarce while some portions of frequency bands suffer from low utilization, the design of cognitive radio (CR) has recently been urged, which allows opportunistic usage of licensed bands for secondary users without interference with primary users. Spectrum sensing is fundamental for a secondary user to find a specific available spectrum hole. Cooperative spectrum sensing is more accurate and more widely used since it obtains helpful reports from nodes in different locations. However, if some nodes are compromised and report false sensing data to the fusion center on purpose, the accuracy of decisions made by the fusion center can be heavily impaired. Weighted sequential probability ratio test (WSPRT), based on a credit evaluation system to restrict damage caused by malicious nodes, was proposed to address such a spectrum sensing data falsification (SSDF) attack at the price of introducing four times more sampling numbers. In this paper, we propose two new schemes, named enhanced weighted sequential probability ratio test (EWSPRT) and enhanced weighted sequential zero/one test (EWSZOT), which are robust against SSDF attack. By incorporating a new weight module and a new test module, both schemes have much less sampling numbers than WSPRT. Simulation results show that when holding comparable error rates, the numbers of EWSPRT and EWSZOT are 40% and 75% lower than WSPRT, respectively. We also provide theoretical analysis models to support the performance improvement estimates of the new schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2067-2080
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• 2016

Cooperative spectrum sensing (CSS) for vacant licensed bands is one of the key techniques in cognitive radio networks. Currently, sequential probability ratio test scheme (SPRT) is considered as a powerful soft decision approach to improve the sensing result for CSS. However, SPRT assumes all secondary users (SU) are honest, and thus offering opportunities for malicious SUs to launch the spectrum sensing data falsification attack (SSDF attack). To combat such misbehaved behaviors, recent efforts have been made to trust mechanism. In this paper, we argue that powering SPRT with traditional trust mechanism is not enough. Dynamic SSDF attackers can maintain high trust in an alternant process of submitting honest or false sensing data, resulting in difficultly detecting them. Noting that the trust value of dymamic SSDF attackers behave highly volatile, a novel trusted SPRT scheme (VSPRT) based on volatility decay analysis is proposed in this paper to mitigate the harmful effect of dynamic SSDF attackers in the process of the soft-decision data fusion, and thus improving the accuracy of the final sensing result. Simulation results show that the VSPRT scheme outperforms the conventional SPRT schemes.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.4
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• pp.416-422
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• 2011

In this paper, we use hard decision method for cooperative spectrum sensing. Sensing performance adopting hard decision is lower than soft decision but system load is low and the process is relatively simple when the combining scheme is hard decision compared to soft decision. In order to improve sensing performance, we propose optimal hard decision method applying weight that is based on a probability of individual sensing. Unlike conventional hard decision, we try to improve sensing performance applying weight and show the performance of the proposed method from the simulation results and performance analysis. The signal of licensed user is OFDM signal and the wireless channel between a licensed user and CR systems is modeled as Gaussian channel.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.62-65
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• 2018

This paper comes out with the study on sensing data collection strategy in a Software-Defined Mobile Edge vehicular networking. The two cooperative data dissemination are Direct Vehicular cloud mode and edge cell trajectory prediction decision mode. In direct vehicular cloud, the vehicle observe its neighboring vehicles and sets up vehicular cloud for cooperative sensing data collection, the data collection output can be transmitted from vehicles participating in the cooperative sensing data collection computation to the vehicle on which the sensing data collection request originate through V2V communication. The vehicle on which computation originate will reassemble the computation out-put and send to the closest RSU. The SDMEVN (Software Defined Mobile Edge Vehicular Network) Controller determines how much effort the sensing data collection request requires and calculates the number of RSUs required to support coverage of one RSU to the other. We set up a simulation scenario based on realistic traffic and communication features and demonstrate the scalability of the proposed solution.

• Journal of information and communication convergence engineering
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• v.14 no.1
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• pp.1-8
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• 2016

Spectrum sensing in cognitive radio networks allows secondary users to sense the unused spectrum without causing interference to primary users. Cognitive radio requires more accurate sensing results from unused portions of the spectrum. Accurate spectrum sensing techniques can reduce the probability of false alarms and misdetection. In this paper, a two-stage spectrum sensing scheme is proposed for cooperative spectrum sensing in cognitive radio networks. In the first stage, spectrum sensing is executed for each secondary user using energy detection based on double adaptive thresholds to determine the spectrum condition. If the energy value lies between two thresholds, a fuzzy logic scheme is applied to determine the channel conditions more accurately. In the second stage, a fusion center combines the results of each secondary user and uses a fuzzy logic scheme for combining all decisions. The simulation results show that the proposed scheme provides increased sensing accuracy by about 20% in some cases.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.996-1015
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• 2016

A common concern regarding cooperative spectrum sensing (CSS) schemes is the occupied bandwidth and the energy consumption during the transmissions of sensing information to the fusion center over the reporting control channels. This concern is intensified if the number of cooperating secondary users in the network is large. This article presents a new fusion strategy for a CSS scheme, aiming at increasing the energy efficiency of a recently proposed bandwidth-efficient fusion scheme. Analytical results and computational simulations unveil a high increase in energy efficiency when compared with the original approach, yet achieving better performances in some situations, and lower implementation complexity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.7
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• pp.1234-1238
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• 2015

We propose cooperative spectrum sensing schemes based on sub-Nyquist sampling. As compressed sensing has recently attracted great attention, sparsity order estimation techniques also has been widely investigated. Thus, assuming that the sparsity order of channel occupancy can be obtained, we mathematically analyze the detection performance of sub-Nyquist sampling schemes according to various sampling rates and cooperative spectrum sensing schemes. Simulation results verify the performance of the proposed schemes.