• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3335-3356
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• 2015

In this paper, we analyze the connectivity of cognitive radio ad-hoc networks in a log-normal shadow fading environment. Considering secondary user and primary user's locations and primary user's active state are randomly distributed according to a homogeneous Poisson process and taking into account the spectrum sensing efficiency of secondary user, we derive mathematical models to investigate the connectivity of cognitive radio ad-hoc networks in three aspects and compare with the connectivity of ad-hoc networks. First, from the viewpoint of a secondary user, we study the communication probability of that secondary user. Second, we examine the possibility that two secondary users can establish a direct communication link between them. Finally, we extend to the case of finding the probability that two arbitrary secondary users can communicate via multi-hop path. We verify the correctness of our analytical approach by comparing with simulations. The numerical results show that in cognitive radio ad-hoc networks, high fading variance helps to remarkably improve connectivity behavior in the same condition of secondary user's density and primary user's average active rate. Furthermore, the impact of shadowing on wireless connection probability dominates that of primary user's average active rate. Finally, the spectrum sensing efficiency of secondary user significantly impacts the connectivity features. The analysis in this paper provides an efficient way for system designers to characterize and optimize the connectivity of cognitive radio ad-hoc networks in practical wireless environment.

• Journal of information and communication convergence engineering
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• v.17 no.1
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• pp.21-40
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• 2019

This paper presents a comprehensive survey of various artificial intelligence (AI) techniques implemented in cognitive radio engine to improve cognition capability in cognitive radio networks (CRNs). AI enables systems to solve problems by emulating human biological processes such as learning, reasoning, decision making, self-adaptation, self-organization, and self-stability. The use of AI techniques is studied in applications related to the major tasks of cognitive radio including spectrum sensing, spectrum sharing, spectrum mobility, and decision making regarding dynamic spectrum access, resource allocation, parameter adaptation, and optimization problem. The aim is to provide a single source as a survey paper to help researchers better understand the various implementations of AI approaches to different cognitive radio designs, as well as to refer interested readers to the recent AI research works done in CRNs.

• Journal of information and communication convergence engineering
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• v.11 no.4
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• pp.223-228
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• 2013

Cognitive radio has been recently considered a promising technology to improve spectrum utilization by enabling secondary access to licensed bands that are not used by primary users temporarily or spatially. A prerequisite to this secondary access is the lack of interference to the primary system. This requirement makes spectrum sensing a key process for cognitive radio. In this study, we consider amplify and forward (AF)-based cooperative spectrum sensing for cognitive radio networks where multiple relay nodes are utilized to amplify and forward the primary user signal for better spectrum sensing, and maximum ratio combining is used for fusion detection by a cognitive coordinator. Further, the detection probability and the bit error rate of AF-based cooperative spectrum sensing are analyzed in fading multiple cognitive relay channels. The simulation results show that the AF-based cooperative spectrum sensing scheme outperforms the conventional scheme.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.417-427
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• 2017

Power allocation is an important factor for cognitive radio networks to achieve higher communication capacity and faster equilibrium. This paper considers power allocation problem to each cognitive user to maximize capacity of the cognitive systems subject to the constraints on the total power of each cognitive user and the interference levels of the primary user. Since this power control problem can be formulated as a mixed-integer nonlinear programming (NP) equivalent to variational inequality (VI) problem in convex polyhedron which can be transformed into complementary problem (CP), we utilize modified projection method to solve this CP problem instead of finding NP solution and give a power control allocation algorithm with a subcarrier allocation scheme. Simulation results show that the proposed algorithm performs well and effectively reduces the system power consumption with almost maximum capacity while achieve Nash equilibrium.

• Journal of Advanced Navigation Technology
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• v.13 no.2
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• pp.201-207
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• 2009

Recently effective spectrum resource technologies have been studied using a game theorectical approach for cognitive radio networks. Radio resource management is required an effective scheme because the performance of a radio communication system much depends on it's effectiveness. In this paper, we suggest a game theoretical algorithm for adaptive power control which is required an effect scheme in cognitive radio networks. It will be a distributed network. In the network distributed cognitive radio secondary users require an adaptive power control. There are many results which are suggested some possibility of game theoretical approaches for communication resource sharing. However, we suggest a practical game algorithm to achieve Nash equilibrium of all secondary users using a Nash equilibrium theorem in this paper. Particularly, a game model was analyzed for adaptive power control of a cognitive radio network, which is involved in DSSS (Direct Sequence Spread Spectrum) techniques. In case of K=63 and N=12 in the DSSS network, the number of iteration was less than maximum 200 using the suggested algorithm.

• Journal of information and communication convergence engineering
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• v.9 no.1
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• pp.27-31
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• 2011

This paper describes the optimization of spectrum sensing in terms of the throughput of a cognitive radio (CR) system. Dealing with the optimization problem of spectrum sensing, this paper evaluates the throughput of a CR system by considering such situations as the penalty time of a channel search and incumbent user (IU) detection delay caused by a missed detection of an incumbent signal. Also, this paper suggests a serial channel search scheme as the search method for a vacant channel, and derives its mean channel search time by considering the penalty time due to the false alarm of a vacant channel search. The numerical results suggest the optimum sensing time of the channel search process using the derived mean channel search time of a serial channel search in the case of a sensing hardware structure with single radio frequency (RF) path. It also demonstrates that the average throughput is improved by two separate RF paths in spite of the hardware complexity of an RF receiver.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.464-468
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• 2007

In cognitive radio systems, secondary users, unlicensed users, can use primary users' spectrum to increase spectrum efficiency. At that time, the systems must satisfy primary users' QoS. When secondary users use cognitive radio systems, secondary users communication can be terminated, because of satisfying primary users' QoS. However, secondary users' communication terminating is not good for both secondary users and whole systems. So, cognitive radio systems need an efficient algorithm for secondary users of admission control and keeping connections. In this paper, we present an algorithm which consist of two part, admission control and connections control.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.6
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• pp.29-35
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• 2009

An efficient stochastic channel selection algorithm for cognitive radio networks is proposed and analyzed in this paper. With the new algorithm utilizing quality of channels, the stationary level of the channels in idle state and history performance, we can find the best channel for secondary users to transmit data. Moreover, this method not only restricts channel switching of secondary users but also adapts to random resource environment of cognitive radio network. The advantages of the proposed algorithm are demonstrated clearly through computer simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.12
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• pp.1755-1757
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• 2013

Dynamically exploiting unused-spectrum, cognitive radio has been proposed to solve spectrum utilization problem. In cognitive radio, it is important to minimize the interference to primary service as well as to provide efficient channel allocation. In this paper, we propose a multi-channel allocation scheme based on spectrum hole prediction. Proposed scheme considered both interference length and channel capacity to limit the interference to primary user as well as to enhance system performance. Simulation results show the proposed scheme improves the system throughput.

• Journal of Satellite, Information and Communications
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• v.4 no.2
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• pp.5-11
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• 2009

In this paper, we propose our design of adaptive resource allocation in the cognitive radio network assisted by satellite to improve the performance of Cognitive Radio user. Most of today’s telecommunication network operates in a fixed, licensed frequency band using a specific spectrum access network. However, the spectrum is not always used all the time, all the band. It causes the inefficiency in the spectrum usage. Thus, cognitive radio network is proposed to solve these spectrum inefficiency problems. The cognitive radio users (secondary users) are coexistent with primary users (PUs) who are licensed. That cognitive radio network is considered as lower priority comparing with primary user. So, the operation of the cognitive radio network is limited to interference constraints. Especially, when the number of secondary users increases, CCI among SUs will increase as well as interference to PU. That motivates our objective to improve the performance even if cognitive radio users increase. To solve this problem, we suggest an adaptive resource allocation scheme to improve the performance of cognitive radio network assisted by satellite. Through this algorithm, we can improve the cognitive radio network performance. And the simulation results confirm the effectiveness of our proposed algorithm.