• Journal of Communications and Networks
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• v.17 no.4
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• pp.406-418
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• 2015

Cognitive radio networks (CRNs) have emerged as a promising solution to the problem of spectrum under utilization and artificial radio spectrum scarcity. The paradigm of dynamic spectrum access allows a secondary network comprising of secondary users (SUs) to coexist with a primary network comprising of licensed primary users (PUs) subject to the condition that SUs do not cause any interference to the primary network. Since it is necessary for SUs to avoid any interference to the primary network, PU activity precludes attempts of SUs to access the licensed spectrum and forces frequent channel switching for SUs. This dynamic nature of CRNs, coupled with the possibility that an SU may not share a common channel with all its neighbors, makes the task of multicast routing especially challenging. In this work, we have proposed a novel multipath on-demand multicast routing protocol for CRNs. The approach of multipath routing, although commonly used in unicast routing, has not been explored for multicasting earlier. Motivated by the fact that CRNs have highly dynamic conditions, whose parameters are often unknown, the multicast routing problem is modeled in the reinforcement learning based framework of learning automata. Simulation results demonstrate that the approach of multipath multicasting is feasible, with our proposed protocol showing a superior performance to a baseline state-of-the-art CRN multicasting protocol.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3775-3788
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• 2014

With the increasing number of the wireless and mobile networks, the way that people use the Internet has changed substantively. Wireless multimedia services, such as wireless video streaming, mobile video game, and mobile voice over IP, will become the main applications of the future wireless Internet. To accommodate the growing volume of wireless data traffic and multimedia services, cognitive radio (CR) and Information-Centric Network (ICN) have been proposed to maximize the utilization of wireless spectrum and improve the network performance. Although CR and ICN have high potential significance for the future wireless Internet, few studies have been conducted on collaborative operations of CR and ICN. Due to the lack of infrastructure support in multi-hop ad hoc CR networks, the problem is more challenging for video streaming services. In this paper, we propose a Cross-layer Video Streaming Mechanism (CLISM) for Cognitive Radio Ad Hoc Information Centric Networks (CRAH-ICNs). The CLISM included two distributed schemes which are designed for the forwarding nodes and receiving nodes in CRAH-ICNs. With the cross-layer approach, the CLISM is able to self-adapt the variation of the link conditions without the central network controller. Experimental results demonstrate that the proposed CLISM efficiently adjust video transmission policy under various network conditions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.6B
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• pp.358-366
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• 2007

Recently, FCC(Federal Communications Commission) has considered for that unlicensed device leases licensed devices' channel to overcome shortage of communication channels. Therefore, IEEE 802.22 WRAN(Wireless Regional Area Networks) working group progresses CR (Cognitive Radio) technique that is able to sense and adopt void channels that are not being occupied by the licensed devices. Channel selection is of the utmost importance because it can affect the whole system performance in CR network. Thus, we propose a policy-based dynamic channel selection architecture for cognitive radio network to achieve an efficient communication. We propose three kinds of method for channel selection; the first one is weighted channel selection, the second one is sequential channel selection, and the last one is combined channel selection. We can obtain the optimum channel list and allocates channels dynamically using the proposed protocol.

• Journal of information and communication convergence engineering
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• v.13 no.4
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• pp.221-227
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• 2015

Spectrum sensing plays an essential role in a cognitive radio network, which enables opportunistic access to an underutilized licensed spectrum. In conventional cooperative spectrum sensing (CSS), all cognitive users (CUs) in the network spend the same amount of time on spectrum sensing and waste time in remaining silent when other CUs report their sensing results to the fusion center. This problem is solved by the superposition cooperative spectrum sensing (SPCSS) scheme, where the sensing time of a CU is extended to the reporting time of the other CUs. Subsequently, SPCSS assigns the CUs different sensing times and thus affects both the sensing performance and the throughput of the system. In this paper, we propose an algorithm to determine the optimal sensing time of each CU for SPCSS that maximizes the achieved system throughput. The simulation results prove that the proposed scheme can significantly improve the throughput of the cognitive radio network compared with the conventional CSS.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2755-2773
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• 2015

Cooperative spectrum sensing increases the detection performance in a cognitive radio network, based on the number of sensing nodes. However, as the number of sensing nodes increases, the reporting overhead linearly increases. This paper proposes two kinds of cooperative spectrum sensing with limited reporting in a centralized cognitive radio network, a soft combination with threshold-based reporting (SC-TR) and a soft combination with contention-based reporting (SC-CR). In the proposed SC-TR scheme, each sensing node reports its sensing result to the fusion center through its own reporting channel only if the observed energy value is higher than a decision threshold. In the proposed SC-CR scheme, sensing nodes compete to report their sensing results via shared reporting channels. The simulation results show that the proposed schemes significantly reduce the reporting overhead without sacrificing the detection performance too much.

• Journal of KIISE
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• v.42 no.1
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• pp.130-137
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• 2015

With the rapid increase of energy consumption and environmental problems, the need for green techniques is increasing. Network coding can provide a solution by reducing unnecessary data transmission and by estimating traffic patterns. In addition, it can amplify the synergy with the cognitive radio network (CR) since the CR has recognition and optimal decision functionalities. In this paper, we propose a network coding based green cognitive radio network. With the simulations, we show that the proposed scheme is up to 25% better than the previous work.

• Journal of Broadcast Engineering
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• v.21 no.1
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• pp.113-116
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• 2016

Cognitive radio network technology is that secondary (unlicensed) users use the spectrum of primary (licensed) users without interfering primary communication. In this paper, we propose multiple access scheme for a cognitive radio network, where multiple secondary users access spectrum of one primary user. We consider two types of multiple access scheme, one is p-persistent and one is non-persistent, and apply these two schemes in the secondary network. For each multiple access scheme, total throughput of secondary network is derived and verified by Monte Carlo simulation. Simulation results show that maximum total throughput of the secondary network is achieved when channel access probability or the number of maximum waiting frames is chosen appropriately.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.13-26
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• 2023

Recently, the development of wireless network technologies has been advancing in several directions: increasing data transmission speed, enhancing user mobility, expanding the range of services offered, improving the utilization of the radio frequency spectrum, and enhancing the intelligence of network and subscriber equipment. In this research, a series of contradictions has emerged in the field of wireless network technologies, with the most acute being the contradiction between the growing demand for wireless communication services (on operational frequencies) and natural limitations of frequency resources, in addition to the contradiction between the expansions of the spectrum of services offered by wireless networks, increased quality requirements, and the use of traditional (outdated) management technologies. One effective method for resolving these contradictions is the application of artificial intelligence elements in wireless telecommunication systems. Thus, the development of technologies for building intelligent (cognitive) radio and cognitive wireless networks is a technological imperative of our time. The functions of artificial intelligence in prospective wireless systems and networks can be implemented in various ways. One of the modern approaches to implementing artificial intelligence functions in cognitive wireless network systems is the application of fuzzy logic and fuzzy processors. In this regard, the work focused on exploring the application of fuzzy logic in prospective cognitive wireless systems is considered relevant.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.989-990
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• 2012

• Journal of the Korean Society for Railway
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• v.12 no.1
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• pp.45-54
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• 2009

TETRA(Terrestrial Trunked Radio) is the standard of D-TRS(Digital Trunked Radio System) developed by the ETSI(European Telecommunications Standards Institute). Currently, TETRA has been selected as Electric Power IT Wireless Backbone Network. Traditional distribution automation system has used the wireless network of Mobile Service Provider using CDMA(Code-Division Multiple Access) and WCDMA(Wideband CDMA) modem. Therefore, the development of gateway platform is indispensable according to the change to TETRA network. In this paper, we propose an embedded Linux-based Gateway platform for transmitting Industrial Electric Power IT protocol using TETRA network.