• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.3
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• pp.208-216
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• 2018

In this paper, an LLC resonant converter employing two coupled inductors on the secondary side of the converter is proposed. The conventional LLC converter exhibits serious power loss during secondary winding of the transformer because of generation of tremendous output current ripples. To overcome this problem, an LLC resonant converter with a current doubler as a rectifying circuit was recently proposed. However, the current-doubler rectifying circuit requires coupled inductors with a high coupling ratio to retain the designed resonance characteristics. Therefore, an additional hardware filter is required at the output stage to address large output current ripples. Additional design procedures are also necessary because the inductance component of the added filter affects the designed resonant network. To solve this issue, an LLC resonant converter employing two coupled inductors is proposed in this paper. Mathematical analysis shows that the proposed secondary-side current-doubler circuit does not affect the designed resonance characteristics. The operating principles and theoretical analyses are proven through a simulation and experiments with a 54 V/28 A prototype.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2686-2708
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• 2020

This paper investigates the energy efficiency of energy harvesting (EH) bidirectional cooperative sensor networks, in which the considered system model enables the uplink information transmission from the sensor (SN) to access point (AP) and the energy supply for the amplify-and-forward (AF) relay and SN using power-splitting (PS) or time-switching (TS) protocol. Considering the minimum EH activation constraint and quality of service (QoS) requirement, energy efficiency is maximized by jointly optimizing the resource division ratio and transmission power. To cope with the non-convexity of the optimizations, we propose the low complexity iterative algorithm based on fractional programming and alternative search method (FAS). The key idea of the proposed algorithm first transforms the objective function into the parameterized polynomial subtractive form. Then we decompose the optimization into two convex sub-problems, which can be solved by conventional convex programming. Simulation results validate that the proposed schemes have better output performance and the iterative algorithm has a fast convergence rate.

• Proceedings of the KIEE Conference
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• 2004.10a
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• pp.160-163
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• 2004

A passive lossless turn-on/turn-off snubber network is proposed for the boost PWM converter. Previous AC/DC PFC Boost Converter perceives feed forward signal of output for average current-mode control. Previous Boost Convertor, the Quantity of input current will be decreased by the decrease of output current in light load, and also Power factor comes to be decreased. Also the efficiency of converter will be decreased by the decrease of power factor. The proposed converter presents the good PFC, low line current harmonic distortions and tight output voltage regulations using energy recovery circuit. All of the semiconductor devices in the converter are turned on under exact or near zero voltage switching(ZVS). No additional voltage and current stresses on the main switch and main diode occur. To show the superiority of this converter is verified through the experiment with a 640W, 100kHz prototype converter.

• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.125-131
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• 2021

In recent years, Convolutional Neural Networks (CNNs) have achieved outstanding performance in the fields of computer vision such as image classification, object detection, visual quality enhancement, etc. However, as huge amount of computation and memory are required in CNN models, there is a limitation in the application of CNN to low-power environments such as mobile or IoT devices. Therefore, the need for neural network compression to reduce the model size while keeping the task performance as much as possible has been emerging. In this paper, we propose a method to compress CNN models by combining matrix decomposition methods of LR (Low-Rank) approximation and CP (Canonical Polyadic) decomposition. Unlike conventional methods that apply one matrix decomposition method to CNN models, we selectively apply two decomposition methods depending on the layer types of CNN to enhance the compression performance. To evaluate the performance of the proposed method, we use the models for image classification such as VGG-16, RestNet50 and MobileNetV2 models. The experimental results show that the proposed method gives improved classification performance at the same range of 1.5 to 12.1 times compression ratio than the existing method that applies only the LR approximation.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.1-12
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• 2020

Low-Orbit satellite mobile networks can provide services through miniaturized terminals with low transmission power, which can be used as reliable means of communication in the national public disaster network and defense sector. However, the high traffic environment in the emergency preparedness situation increases the new call blocking probability and the handover failure probability of the satellite network, and the increase of the handover failure probability affects the QoS because low orbit satellites move in orbit at a very high speed. Among the channel allocation methods of satellite communication, the FCA shows relatively better performance in a high traffic environment than DCA and is suitable for emergency preparedness situations, but in order to optimize QoS when traffic increases, the new call blocking and the handover failure must be minimized. In this paper, we propose LEO-DBC (LEO satellite dynamic beam width control) technique, which improves QoS by adaptive adjustment of beam width of low-orbit satellites and call time of terminals by improving FCA-QH method. Through the LEO-DBC technique, it is expected that the QoS of the mobile satellite communication network can be optimally maintained in high traffic environments in emergency preparedness situations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.147-153
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• 2018

Beacon enables one to measure distance indoors based on low-power Bluetooth low energy (BLE) technology, while GPS (Global Positioning System) only can be used outdoors. In measuring indoor distance using Beacon, RSSI (Received Signal Strength Indication) is considered as the one of the key factors, however, it is influenced by various environmental factors so that it causes the huge gap between the estimated distance and the real. In order to handle this issue, we propose the adaptive ANN (Artificial Neural Network) based approach to measuring the exact distance using Beacon. First, we has carried out the preprocessing of the RSSI signals by applying the extended Kalman filter and the signal stabilization filter into decreasing the noise. Then, we suggest the multi-layered ANNs, each of which layer is learned by specific training data sets. The results showed an average error of 0.67m, a precision of 0.78.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12A
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• pp.1198-1206
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• 2010

Recently smart phone and tablet PC are regarded as the most valuable mobile devices, so the demand of customers for multimedia supporting has been greatly increased. The network operators are now considering the deployment of relay stations ensuring low installation costs for its service cell to improve the cell capacity. Enhancing the relay stations, however, increases intra-cell interference, which is affecting the quality of service and outage ratio. In this paper, we present MPFR(Multihop Partial Frequency reuse) as the new frequency reuse scheme to increase cell throughput while maintaining low outage ratio for the OFDMA cellular multihop networks. Dynamic power control is also introduced to improve cell capacity. Overall cell throughput and outage ratio are observed by the simulation, and comparison between MPFR and conventional multihop frequency reuse schemes is convincing the performance enhancement.

• Journal of KIISE:Information Networking
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• v.30 no.2
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• pp.252-259
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• 2003

In the case of link congestion, most of the existing ad-hoc routing protocols like AODV and DSR do not try to discover a new route if there is no change in the network topology. Hence, with low mobility, traffic may get concentrated on some specific nodes. Since mobile devices have low battery power and low computing capability, traffic concentration on a specific node is not a desirable phenomenon. Therefore, in this paper, we propose a new protocol called SLAP (Simple Load-balancing Ad-hoc routing Protocol) which resolves the traffic concentration problem by letting each node check its own load situation and give up its role as a packet forwarder gracefully in the case of high traffic load. We compare the performance of SLAP with that of AODV and DSR in terms of the forwarding traffic distribution.

• Journal of the Korea Society of Computer and Information
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• v.13 no.2
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• pp.203-210
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• 2008

Home networking has been noticed as a key technology for the home automation because it is possible to remotely monitor and control the in-house appliances and devices through the network. Wireless home networking method is easily applied to the conventional houses compared to the wired home networking method because of low cost and small effort due to no extra wired works. Especially, home networking using the ZigBee protocol is one of the most attractive technologies in the wireless networking area because of its low cost and low power consumption characteristics. However, there are a lot of practical problems to be solved in implementing the ZigBee module and constructing the wireless network. In this paper, one of the practical structures of the hardware and software modules for implementing the ZigBee protocol is proposed. Moreover, problems in constructing the home networking with the proposed ZigBee module are introduced, and the effective solutions to solve these problems are described through various tests.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.51-61
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• 2021

In the era of the 4th industrial revolution symbolized by the Internet of Things, big data and artificial intelligence, various embedded devices are increasing exponentially. These devices have communication functions despite their low specifications, so the possibility of personal information leakage is increasing, and security threats are also increasing. Embedded devices can have security issues at most levels, from hardware to services over the network. In addition, it is difficult to apply general security techniques because it has characteristics of resource constraints such as low specifications and low power, and the related technology has not been standardized. In this study, we present vulnerabilities and possible problems and considerations in applying SDN to embedded devices in consideration of structural characteristics and real-world discovered cases. This study presents vulnerabilities and possible problems and considerations when applying SDN to embedded devices. From a hardware perspective, we consider the problems of Wi-Fi chips and Bluetooth, the problems of open flow implementation, SDN controllers, and examples of structural properties. SDN separates the data plane and the control plane, and provides a standardized interface between the two, enabling efficient communication control. It can respond to the security limitations of existing network technologies that are difficult to respond to rapid changes.