• ETRI Journal
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• v.45 no.6
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• pp.1065-1078
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• 2023

In vehicular networks, diverse safety information can be shared among vehicles through internet connections. In vehicle-to-internet communications, vehicles on the road are wirelessly connected to different cloud networks, thereby accelerating safety information exchange. Onboard sensors acquire traffic-related information, and reliable intermediate nodes and network services, such as navigational facilities, allow to transmit safety information to distant target vehicles and stations. Using vehicle-to-network communications, we minimize delays and achieve high accuracy through consistent connectivity links. Our proposed approach uses intermediate nodes with two-hop separation to forward information. Target vehicle detection and routing of safety information are performed using machine learning algorithms. Compared with existing vehicle-to-internet solutions, our approach provides substantial improvements by reducing latency, packet drop, and overhead.

• International Journal of Computer Science & Network Security
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• v.24 no.8
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• pp.139-144
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• 2024

VANETs have become one of the most attractive research areas in the world of wireless networks in recent years. Indeed, vehicular networks have become capable of optimizing road traffic, which significantly reduces the number of accidents through notifications exchanged between nearby vehicles. The routing function based on the opportunistic algorithm is a critical part of the vehicle's communication system and will therefore be an ideal target for attacks that could aim to prevent alert messages from reaching their destination, and thus endanger human lives. The black hole attack is a major threat to the security of VANETs. The main idea of this paper focuses on the analysis of this type of attack in VANETs using Discrete-Time Markov Chains (DTMC). and deduce at the end the effect of the number of malicious nodes on the delivery rate in the network.

• Knowledge Management Research
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• v.13 no.2
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• pp.1-18
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• 2012

This article describes how attributes of social network contribute to enhance innovativeness of corporation which is considered to be one of the competitive factors in this global market. The study especially focused on employees' formal and informal communication that is expected to play a mediating role between the factors. 211 employees were randomly selected to participate in an online survey. The result has shown that the static correlation exists between social network, communication, and innovativeness. Closeness of social network was the only influencing factor on communication and innovativeness, and had a partial mediated effect between social network and innovativeness. Based on the suggested contribution for HRD intervention, various communication channels should be developed and supported in order to enhance innovation among social networks in organizations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.5
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• pp.985-988
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• 2017

Magnetic induction (MI) based communication is one of the near-field communication techniques, which makes use of induced magnetic fields. In order to develop the MI based underwater communication networks, we evaluate and compare the loss performance between direct-MI and MI-waveguide in underwater environment.

• ETRI Journal
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• v.41 no.3
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• pp.326-336
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• 2019

A wireless power transfer technique can solve the power capacity problem in wireless rechargeable sensor networks (WRSNs). The charging strategy is a wide-spread research problem. In this paper, we propose a demand-based charging strategy (DBCS) for WRSNs. We improved the charging programming in four ways: clustering method, selecting to-be-charged nodes, charging path, and charging schedule. First, we proposed a multipoint improved K-means (MIKmeans) clustering algorithm to balance the energy consumption, which can group nodes based on location, residual energy, and historical contribution. Second, the dynamic selection algorithm for charging nodes (DSACN) was proposed to select on-demand charging nodes. Third, we designed simulated annealing based on performance and efficiency (SABPE) to optimize the charging path for a mobile charging vehicle (MCV) and reduce the charging time. Last, we proposed the DBCS to enhance the efficiency of the MCV. Simulations reveal that the strategy can achieve better performance in terms of reducing the charging path, thus increasing communication effectiveness and residual energy utility.

• Electronics and Telecommunications Trends
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• v.39 no.5
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• pp.86-97
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• 2024

With the advancement of quantum computers and increasing importance of cybersecurity, quantum cryptography has become an essential technology in quantum world. The success of ground-to-satellite quantum communication in the range of 4,600 km has been reported, and intercountry quantum cryptography connecting the UK and Ireland has been demonstrated. In the European Union, OpenQKD has established 18 testbeds for quantum communication in 12 countries. Through the progress from experimental to pilot networks, quantum cryptography testbeds have begun to provide networks for commercial services, such as finance, healthcare, and government administration. Similarly, the Republic of Korea launched a quantum communication testbed project to accelerate the development of quantum communication devices and materials. The project also aims to support the relevant companies and services in the verification and certification of security functionalities operated by the National Intelligence Service. We review the status of quantum communication testbeds in 16 countries.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4145-4164
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• 2016

Energy harvesting is an increasingly attractive source of power for cellular networks, and can be a promising solution for green networks. In this paper, we consider a cellular network with power beacons powering multiple mobile terminals with microwave power transfer in energy beamforming. In this network, the power beacons are powered by grid and renewable energy jointly. We adopt a dual-level control architecture, in which controllers collect information for a core controller, and the core controller has a real-time global view of the network. By implementing the water filling optimized power allocation strategy, the core controller optimizes the energy allocation among mobile terminals within the same cluster. In the proposed green energy cooperation paradigm, power beacons dynamically share their renewable energy by locally injecting/drawing renewable energy into/from other power beacons via the core controller. Then, we propose a new water filling optimized green energy cooperation management strategy, which jointly exploits water filling optimized power allocation strategy and green energy cooperation in cellular networks. Finally, we validate our works by simulations and show that the proposed water filling optimized green energy cooperation management strategy can achieve about 10% gains of MT's average rate and about 20% reduction of on-grid energy consumption.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1500-1506
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• 2020

In this paper, we study a scheduling problem based on reinforcement learning for overlay device-to-device (D2D) communication networks. Even though various technologies for D2D communication networks using Q-learning, which is one of reinforcement learning models, have been studied, Q-learning causes a tremendous complexity as the number of states and actions increases. In order to solve this problem, D2D communication technologies based on Deep Q Network (DQN) have been studied. In this paper, we thus design a DQN model by considering the characteristics of wireless communication systems, and propose a distributed scheduling scheme based on the DQN model that can reduce feedback and signaling overhead. The proposed model trains all parameters in a centralized manner, and transfers the final trained parameters to all mobiles. All mobiles individually determine their actions by using the transferred parameters. We analyze the performance of the proposed scheme by computer simulation and compare it with optimal scheme, opportunistic selection scheme and full transmission scheme.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.468-473
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• 1999

Neural networks for adaptive channel equalizers have been resorted to recently in digital communication systems. In this paper, the characteristics and the application areas and etc. for neural networks as adaptive channel equalizers are examined through simple examples.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1249-1254
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• 2016

Recently, there have been many researches which can achieve high data rate in multi-user massive MIMO networks while reducing the complexity in terms of both hardware and algorithm. In addition, many researches have been conduced to reduce the energy consumption in next generation mobile communication networks. In this paper, we thus investigated new transmit antenna selection scheme to achieve low computational complexity and enhance energy efficiency in multi-user massive MIMO networks. First, we introduced the optimal scheme based on Brute-Force searching to maximize the energy efficiency and then proposed new antenna selection scheme to dramatically reduce the computational complexity compared to the optimal scheme. As the number of transmit antennas increases, the complexity of the optimal scheme exponentially increases while the complexity of the proposed scheme linearly increases. Nevertheless, the energy efficiency performance gap between proposed and optimal schemes is not huge.