• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3655-3673
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• 2014

Rendezvous is a process of two or more cognitive radio nodes gathering on the same channel at the same time for a negotiation to establish data communications. This paper discusses rendezvous issues in cognitive radio networks. It details why rendezvous is an issue in cognitive radio networks and how rendezvous works. It classifies channel access methods, and details sequence-based channel-hopping methods. It surveys existing works on blind rendezvous and compares the proposed algorithms in terms of the maximum time to rendezvous. This paper discusses the properties that an efficient channel-hopping rendezvous algorithm should have and illustrates common issues in the existing rendezvous methods. It also explains open research issues in the rendezvous area.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.710-718
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• 2012

The implementation of a common control channel is one of the most challenging issues in cognitive radio networks, since a fully reliable control channel cannot be created without reserving bandwidth specifically for this purpose. In this paper, we investigate a promising solution that exploits the ultra wide band (UWB) technology to let cognitive radio nodes discover each other and exchange control information for establishing a communication link. The contribution of this paper is threefold: (i) We define the communication protocol needed to let cognitive radio nodes discover each other and exchange control information for link set up, (ii) we overcome the gap in coverage, which typically exists between UWB and long-medium range technologies, by using multi-hop communication, (iii) we evaluate the performance of our approach by adopting an accurate channel model and show its benefits with respect to an in-band signaling solution.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11A
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• pp.822-830
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• 2009

The spectrum efficiency of mobile communication networks can be improved dramatically adopting multiple antennas technologies. In order to guarantee the licensed rights of primary user (PU), the cognitive radio system should perform in a relatively low interference manner when it gets access to the spectrum of licensed networks. In this paper, we explore a uniformly distributed circular antenna array to implement beamforming algorithm that is accomplished by optimization method at the base station of cognitive radio networks, and therefore we can suppress the interference to PU by steering quite low transmission power toward PU and constructing a narrow beam toward cognitive user (CU). By reducing the constraint number of the optimization problem, we also propose a null steering algorithm that steers rather low radiation power toward PU, while the other areas in the same cell are covered by radiation power except the local area around PU. It is pursued to reduce the computation load and enlarge the capacity of cognitive radio networks extremely. The simulation results demonstrate that the proposed algorithms process superior performance.

• Journal of Communications and Networks
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• v.14 no.1
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• pp.51-62
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• 2012

The exponential growth in wireless services has resulted in an overly crowded spectrum. The current state of spectrum allocation indicates that most usable frequencies have already been occupied. This makes one pessimistic about the feasibility of integrating emerging wireless services such as large-scale sensor networks into the existing communication infrastructure. Cognitive radio is an emerging dynamic spectrum access technology that can be used for flexibly and efficiently achieving open spectrum sharing. Cognitive radio is an intelligent wireless communication system that is aware of its radio environment and that is capable of adapting its operation to statistical variations of the radio frequency. In ad hoc cognitive radio networks, a common control channel (CCC) is usually used for supporting transmission coordination and spectrum-related information exchange. Determining a CCC in distributed networks is a challenging research issue because the spectrum availability at each ad hoc node is quite different and dynamic due to the interference between and coexistence of primary users. In this paper, we propose a novel CCC selection protocol that is implemented in a distributed way according to the appearance patterns of primary systems and connectivity among nodes. The proposed protocol minimizes the possibility of CCC disruption by primary user activities and maximizes node connectivity when the control channel is set up. It also facilitates adaptive recovery of the control channel when the primary user is detected on that channel.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.50-67
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• 2015

The Cognitive Radio (CR) paradigm in tactical ad hoc networks is an important element of future military communications for network-centric warfare. This paper presents a novel Cognitive Link State Routing protocol for CR-based tactical ad hoc networks. The proposed scheme provides prompt and reliable routes for Primary User (PU) activity through procedures that incorporate two main functions: PU-aware power adaptation and channel switching. For the PU-aware power adaptation, closer multipoint relay nodes are selected to prevent network partition and ensure successful PU communication. The PU-aware channel switching is proactively conducted using control messages to switch to a new available channel based on a common channel list. Our simulation study based on the ns-3 simulator demonstrates that the proposed routing scheme delivers significantly improved performance in terms of average end-to-end delay, jitter, and packet delivery ratio.

• 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.

• The Korean Journal of Community Living Science
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• v.24 no.3
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• pp.301-312
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• 2013

The purpose of this study was to investigate the differences between attentional networks according to sex and reflection-impulsivity in the cognitive styles of young children. The subjects of the study were 78 5-year-old children from the kindergarten or daycare center in Busan(with 40 in the reflection group, and 38 in the impulsivity group). The tests were conducted by using the Mating Familiar Test and the Attentional Network Test for young children. The study has used two independent t-tests to find out the differences between attentional networks according to sex, and reflection-impulsivity in the cognitive styles of young children. The results of this study were as follows. First, the boys with reflection cognitive style were significantly slower than the girls with the same style(t=2.18, p<.05). Second, young children with reflection cognitive style were significantly faster in the case of alerting effects than those with impulsivity cognitive style(t=-2.53, p<.05). The young children with reflection cognitive style were slower than those with impulsivity cognitive style in the case of orienting effect(t=2.04, p<.05). Children with a combination of both conflict effect and reflection cognitive style were significantly faster than those with impulsivity cognitive style(t=-2.89, p<.01). The results of the study suggested that there was a difference between attentional networks according to sex and reflection-impulsivity cognitive styles of young children.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2323-2340
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• 2012

Recent advances in cognitive radio technology have drawn immense attention to higher layer protocols above medium access control, such as transmission control protocol (TCP). Most proposals to improve the TCP performance in cognitive radio (CR) networks have assumed that either all nodes are in CR networks or the TCP sender side is in CR links. In those proposals, lower layer information such as the CR link status could be easily exploited to adjust the congestion window and improve throughput. In this paper, we consider a TCP network in which the TCP sender is located remotely over the Internet while the TCP receiver is connected by a CR link. This topology is more realistic than the earlier proposals, but the lower layer information cannot be exploited. Under this assumption, we propose an enhanced TCP protocol for CR networks called TCP for cognitive radio (TCP-CR) to improve the existing TCP by (1) detection of primary user (PU) interference by a remote sender without support from lower layers, (2) delayed congestion control (DCC) based on PU detection when the retransmission timeout (RTO) expires, and (3) exploitation of two separate scales of the congestion window adapted for PU activity. Performance evaluation demonstrated that the proposed TCP-CR achieves up to 255% improvement of the end-to-end throughput. Furthermore, we verified that the proposed TCP does not deteriorate the fairness of existing TCP flows and does not cause congestions.

• Journal for History of Mathematics
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• v.22 no.3
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• pp.31-44
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• 2009

Anyone wishing to understand cognitive science, a converging science, need to become familiar with three major mathematical landmarks: Turing machines, Neural networks, and $G\ddot{o}del's$ incompleteness theorems. The present paper aims to explore the mathematical foundations of cognitive science, focusing especially on these historical landmarks. We begin by considering cognitive science as a metamathematics. The following parts addresses two mathematical models for cognitive systems; Turing machines as the computer system and Neural networks as the brain system. The last part investigates $G\ddot{o}del's$ achievements in cognitive science and its implications for the future of cognitive science.