• Journal of Advanced Navigation Technology
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• v.21 no.4
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• pp.347-352
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• 2017

In this paper, we propose a method that reduces mobile user's handover call dropping probability by using cognitive radio technology(CR) in cellular - based wireless cognitive radio networks. The proposed method predicts a cell to visit by Ziv-Lempel algorithm, and then supports mobile user with prediction of spectrum holes based on CR technology when allocated channels are short in the cell. We make neural network predict spectrum hole resources, and make handover calls use the resources before initial calls. Simulation results show CR technology has the capability to reduce mobile user handover call dropping probability in cellular mobile communication networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2302-2322
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• 2012

Wireless Body Area Networks (WBANs) are introduced as an enabling technology in tele-health for patient monitoring. Designing an efficient Medium Access Control (MAC) protocol is the main challenge in WBANs because of their various applications and strict requirements such as low level of energy consumption, low transmission delay, the wide range of data rates and prioritizing emergency data. In this paper, we propose a new MAC protocol to provide different requirements of WBANs targeted for medical applications. The proposed MAC provides an efficient emergency response mechanism by considering the correlation between medical signals. It also reduces the power consumption of nodes by minimizing contention access, reducing the probability of the collision and using an efficient synchronization algorithm. In addition, the proposed MAC protocol increases the data rate of the nodes by allocating the resources according to the condition of the network. Analytical and simulation results show that the proposed MAC protocol outperforms IEEE 802.15.4 MAC protocol in terms of power consumption level as well as the average response delay. Also, the comparison results of the proposed MAC with IEEE 802.15.6 MAC protocol show a tradeoff between average response delay and medical data rate.

• Broadcasting and Media Magazine
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• v.12 no.3
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• pp.14-36
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• 2007

다양한 무선 통신 서비스의 등장으로 주파수 자원의 수요가 급증하여 스펙트럼 이용 효율을 극대화하기 위한 새로운 기술 개발의 필요성이 대두되고 있으며, 이에 대한 기술로 Cognitive Radio (CR) 기술이 주목받고 있다. CR 기술은 선택된 주파수 대역에 최적의 QoS를 제공하기 위해서는 먼저 주파수 환경에 적응성을 갖는 스펙트럼 센싱 (Spectrum Sensing) 기술이 필요하며, CR 기술이 적용된 무선 브로드밴드 네트워크 (AWBN : Adaptive Wireless Broadband Network) 모듈은 최근 각광받고 있는 방통융합 솔루션의 Hot Issue인 QoS 보장 홈네트워크 기반의 멀티미디어 전송(TV Portal Service)용 네트워크에 최적화된 솔루션으로 활용될 것으로 기대하고 있을 뿐만 아니라, IEEE 802.22 그룹에서 연구되고 있는 비어있는 TV 대역 및 마이크로폰 대역에 활용될 뿐만 아니라, 기존의 Mobile WiMax에 의한 브로드밴드 네트워크에도 활용 가능하다. 본 고에서는 IEEE 802.22/16d 시스템 규격에 의해 개발된 AWBN 시스템 개발 내용을 기술한다.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.227-237
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• 2014

Throughput scaling laws for two coexisting ad hoc networks with m primary users (PUs) and n secondary users (SUs) randomly distributed in an unit area have been widely studied. Early work showed that the secondary network performs as well as stand-alone networks, namely, the per-node throughput of the secondary networks is ${\Theta}(1/\sqrt{n{\log}n})$. In this paper, we show that by exploiting directional spectrum opportunities in secondary network, the throughput of secondary network can be improved. If the beamwidth of secondary transmitter (TX)'s main lobe is ${\delta}=o(1/{\log}n)$, SUs can achieve a per-node throughput of ${\Theta}(1/\sqrt{n{\log}n})$ for directional transmission and omni reception (DTOR), which is ${\Theta}({\log}n)$ times higher than the throughput with-out directional transmission. On the contrary, if ${\delta}={\omega}(1/{\log}n)$, the throughput gain of SUs is $2{\pi}/{\delta}$ for DTOR compared with the throughput without directional antennas. Similarly, we have derived the throughput for other cases of directional transmission. The connectivity is another critical metric to evaluate the performance of random ad hoc networks. The relation between the number of SUs n and the number of PUs m is assumed to be $n=m^{\beta}$. We show that with the HDP-VDP routing scheme, which is widely employed in the analysis of throughput scaling laws of ad hoc networks, the connectivity of a single SU can be guaranteed when ${\beta}$ > 1, and the connectivity of a single secondary path can be guaranteed when ${\beta}$ > 2. While circumventing routing can improve the connectivity of cognitive radio ad hoc network, we verify that the connectivity of a single SU as well as a single secondary path can be guaranteed when ${\beta}$ > 1. Thus, to achieve the connectivity of secondary networks, the density of SUs should be (asymptotically) bigger than that of PUs.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.3
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• pp.75-83
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• 2011

Cognitive radio (CR) technology is to maximize the spectrum utilization by allocating the unused spectrums to the unlicensed users. This technology enables the sharing of channels among secondary (unlicensed) and primary (licensed) users on a non-interference basis after sensing the vacant channel and as a result, it is possible to harness wireless frequency more efficiently. To enhance the accuracy of sensing, RDSS was suggested. It is a fusion mechanism based on the reputation of sensing nodes and WSPRT (weighted sequential probability ratio test). However, in RDSS, the execution number of WSPRT could increase according to the order of inputted sensing values, and the fast defense against the forged values is difficult. In this paper, we propose a transaction signing-based authentication scheme for secure distributed spectrum sensing to response the forged values. The validity of proposed scheme is provided by BAN logic.

• ETRI Journal
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• v.35 no.4
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• pp.644-654
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• 2013

In this paper, a signal detection scheme for cognitive radio (CR) based on the Bussgang theorem is proposed. The proposed scheme calculates the statistical difference between Gaussian noise and the primary user signal by applying the Bussgang theorem to the received signal. Therefore, the proposed scheme overcomes the noise uncertainty and gives scalable complexity according to the zero-memory nonlinear function for a mobile device. We also present the theoretical analysis on the detection threshold and the detection performance in the additive white Gaussian noise channel. The proposed detection scheme is evaluated by computer simulations based on the IEEE 802.22 standard for the wireless regional area network. Our results show that the proposed scheme is robust to the noise uncertainty and works well in a very low signal-to-noise ratio.

• Journal of KIISE:Information Networking
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• v.37 no.3
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• pp.249-253
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• 2010

Resource of wireless frequency bandwidth is gradually going to be deficient due to explosive increase of traffic and saturated non-licensed frequency band such as ISM. In the contrary, many licensed frequency bands are revealed to be low in utilization by several measurement based researches. To alleviate this inefficiency, a concept of cognitive radio is suggested. Cognitive radio lets non-licensed user exploit the licensed frequency band as long as non-licensed user does not interfere licensed user and as a result, it is possible to harness wireless frequency more efficiently. IEEE 802.22 is the first standard network with cognitive radio technology and it employs Two-Stage channel sensing mechanism to accomplish both enough licensed user protection and efficient channel utilization. In this paper, we analyze the overhead of Two-Stage channel sensing mechanism and identify the influence of channel sensing time to the overhead.

• Journal of Communications and Networks
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• v.16 no.1
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• pp.67-80
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• 2014

Spectrum sensing is vital for secondary unlicensed nodes to coexist and avoid interference with the primary licensed users in cognitive wireless networks. In this paper, we develop models for bounding interference levels from secondary network to the primary nodes within a spectrum sensing framework. Instead of classical stochastic approaches where Poisson point processes are used to model transmitters, we consider a more practical model which takes into account the medium access control regulations and where the secondary Poisson process is judiciously thinned in two phases to avoid interference with the secondary as well as the primary nodes. The resulting process will be a modified version of the Mat$\acute{e}$rn point process. For this model, we obtain bounds for the complementary cumulative distribution function of interference and present simulation results which show the developed analytical bounds are quite tight. Moreover, we use these bounds to find the operation regions of the secondary network such that the interference constraint is satisfied on receiving primary nodes. We then obtain theoretical results on the primary and secondary throughputs and find the throughput limits under the interference constraint.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1951-1975
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• 2023

Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.

• ETRI Journal
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• v.42 no.6
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• pp.846-858
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• 2020

The non-orthogonal multiple access (NOMA) technique offers throughput improvement to meet the demands of the future generation of wireless communication networks. The objective of this work is to further improve the throughput by including an underlay cognitive radio network with an existing multi-carrier NOMA network, using cooperative communication. The throughput is maximized by optimal resource allocation, namely, power allocation, subcarrier assignment, relay selection, user pairing, and subcarrier pairing. Optimal power allocation to the primary and secondary users is accomplished in a way that target rate constraints of the primary users are not affected. The throughput maximization is a combinatorial optimization problem, and the computational complexity increases as the number of users and/or subcarriers in the network increases. To this end, to reduce the computational complexity, a dynamic network resource allocation algorithm is proposed for combinatorial optimization. The simulation results show that the proposed network improves the throughput.