• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.7
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• pp.599-611
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• 2016

This paper proposes a cognitive engine platform that enables dynamic spectrum access(DSA) based on a spectrum sharing system for the military tactical network environment. The current military tactical wireless communication system is increasing need to secure a supplementary wireless spectrum to ensure that multiple wireless networks for different weapon systems co-exist, so that tactical wireless communication between the same or different systems can be operated effectively. This paper examined policy development and research activities engaged by the U.S. and European countries on wireless spectrum sharing to secure more spectrum. It also introduces the current status of cognitive engine development, which is the core technology of tactical wireless communication for DSA. In addition, based on the investigation performed into the latest trends, we propose a platform structure for a cognitive engine based on a spectrum sharing method where more frequencies can be added for tactical radio communication, so that DSA can be realized, and wireless networks of different weapon systems can co-exist.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.7
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• pp.1533-1546
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• 2013

Wireless multicast is considered as an effective transmission mode for the future mobile social contact services supported by Long Time Evolution (LTE). Though wireless multicast has an excellent resource efficiency, its performance suffers deterioration from the channel condition and wireless resource availability. Cognitive Radio (CR) and Device to Device (D2D) are two solutions to provide potential resource. However, resource allocation for cognitive wireless multicast based on D2D is still a great challenge for LTE social networks. In this paper, a joint sub-carriers and power allocation model based on D2D for general cognitive radio multicast (CR-D2D-MC) is proposed for Orthogonal Frequency-Division Multiplexing (OFDM) LTE systems. By opportunistically accessing the licensed spectrum, the maximized capacity for multiple cognitive multicast groups is achieved with the condition of the general scenario of imperfect spectrum sensing, the constrains of interference to primary users (PUs) and an upper-bound power of secondary users (SUs) acting as multicast source nodes. Furthermore, the fairness for multicast groups or unicast terminals is guaranteed by setting a lower-bound number of the subcarriers allocated to cognitive multicast groups. Lagrange duality algorithm is adopted to obtain the optimal solution to the proposed CR-D2D-MC model. The simulation results show that the proposed algorithm improves the performance of cognitive multicast groups and achieves a good balance between capacity and fairness.

• Journal of Broadcast Engineering
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• v.19 no.3
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• pp.415-418
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• 2014

The CBS methodology has been standardized in order to make a rapid broadcast of emergency alert message for cellular users. However, the standard does not specify a retransmission request mechanism in the case that the users fail in receiving the alert message. Therefore, we propose a retransmission request scheme based on cognitive radio for the CBS technology in this letter. The simulation results confirm that our proposed scheme is very suitable for the retransmission method in CBS-based emergency alert broadcast systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1638-1653
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• 2014

A sequential optimization algorithm (SOA) for resource allocation in a cyclic-prefixed single-carrier cognitive relay system is proposed in this study. Both subcarrier pairing (SP) and power allocation are performed subject to a primary user interference constraint to minimize the mean squared error of frequency-domain equalization at the secondary destination receiver. Under uniform power allocation at the secondary source and optimal power allocation at the secondary relay, the ordered SP is proven to be asymptotically optimal in maximizing the matched filter bound on the signal-to-interference-plus-noise ratio. SOA implements the ordered SP before power allocation optimization by decoupling the ordered SP from the power allocation. Simulation results show that SOA can optimize resource allocation efficiently by significantly reducing complexity.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.16 no.27
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• pp.105-111
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• 1993

Human works shift its roll from physical condition to the system supervisory control task In this paper safety-presentation configuration is discussed instead of well-known fault-warning configuration. Of paticular interest was the personal factor which include the cognitive process. Through a performance between each person information processing(d') and decision process($\beta$) was pointed out to explain the sensitivity of personal cognitive process. Impact of uncertainty effect the supervisor having doubt situations. These facts are released by the use of flat fuzzy number of $\beta$ and its learning rate R.

• 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 Information Processing Systems
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• v.10 no.1
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• pp.119-131
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• 2014

In recent literature on traffic scheduling, the combination of the two-dimensional discrete-time Markov chain (DTMC) and the Markov modulated Poisson process (MMPP) is used to analyze the capacity of VoIP traffic in the cognitive radio system. The performance of the cognitive radio system solely depends on the accuracy of spectrum sensing techniques, the minimization of false alarms, and the scheduling of traffic channels. In this paper, we only emphasize the scheduling of traffic channels (i.e., traffic handling techniques for the primary user [PU] and the secondary user [SU]). We consider the following three different traffic models: the cross-layer analytical model, M/G/1(m) traffic, and the IEEE 802.16e/m scheduling approach to evaluate the performance of the VoIP services of the cognitive radio system from the context of blocking probability and throughput.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1333-1343
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• 2016

Spectrum sharing in centrally controlled cognitive radio (CR) networks has been widely studied, however, research on channel access for distributively controlled individual cognitive users has not been fully characterized. This paper conducts an analysis of random channel access of cognitive users controlled in a distributed manner in a CR network. Based on the proposed estimation method, each cognitive user can estimate the current channel condition by using its own Markov-chain model and can compute its own blocking probability, collision probability, and forced termination probability. Using the proposed scheme, CR with distributed control (CR-DC), CR devices can make self-controlled decisions based on the status estimations to adaptively control its system parameters to communicate better.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.10 no.16
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• pp.173-182
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• 1987

Motivation models based on the Psychology have contributed to Predict and understand individual behaviors. During the many period, a various type of motivation models have been experimented by the researchers(i.e., need theory that is the first theory in motivation and equity theory, expectancy theory, reinforcement theory, and goal-setting theory centered on cognitive mechanisms). This article's objectives is to analyze motivation models mentioned above in the point of cognitive views (cognitive processes and cognitive mechanisms). Accordingly, the article's structure is consisted of five parts as follows. Part 1. Introduction. Part 2. The theoritical backgrounds of motivation. Part 3. The major theories of motivation. Part 4. The cognitive analysis of motivation theories. Part 5. Conclusion.

• 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.