• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.382-385
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• 2011

The sensor network technology for core technology of ubiquitous computing is in the spotlight recently, the research on sensor network is proceeding actively which is composed many different sensor node. One of the important condition for design of sensor node is to extend for network life which is to minimize power-consumption under the limited resources of sensor network. This study suggest routing protocol that was used second level cluster structure to reduce power-consumption of sensor node. the first level use the previous routing protocol under the LEACH, second level decide to transmit or not by comparision of data value for Effective Usage, reduce the unnecessary power-consumption.

• ETRI Journal
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• v.40 no.1
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• pp.51-60
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• 2018

In Long Term Evolution (LTE) cellular networks, the transmit power control (TPC) mechanism consists of two parts: the open loop (OL) and closed loop. Most cellular networks consider OL/TPC because of its simple implementation and low operation cost. The analysis of OL/TPC parameters is essential for efficient resource management from the cellular operator's viewpoint. In this work, the impact of the OL/TPC parameters is investigated for homogeneous small cells and heterogeneous small-cell/macrocell network environments. A mathematical model is derived to compute the transmit power at the user equipment, the received power at the eNodeB, the interference in the network, and the received signal-to-interference ratio. Using the analytical platform, the effects of the OL/TPC parameters on the system performance in LTE networks are investigated. Numerical results show that, in order to achieve the best performance, it is appropriate to choose ${\alpha}_{small}=1$ and $P_{o-small}=-100dBm$ in a homogenous small-cell network. Further, the selections of ${\alpha}_{small}=1$ and $P_{o-small}=-100dBm$ in the small cells and ${\alpha}_{macro}=0.8$ and $P_{o-macro}=-100dBm$ in the macrocells seem to be suitable for heterogeneous network deployment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1250-1264
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• 2017

This paper presents the architecture design, implement, experimental validation of a bistatic backscatter wireless communication system in Wi-Fi network. The operating principle is to communicate a tag's data by detecting the power level of the power modulated Wi-Fi packets to be reflected or absorbed by backscatter tag, in interconnecting with Wi-Fi device and Wi-Fi AP. This system is able to provide the identification and sensor data of tag on the internet connectivity without requiring extra device for reading data, because this uses an existing Wi-Fi AP infrastructure. The backscatter tag consists of Wi-Fi energy harvesting part and a backscatter transmitter/a power-detecting receiver part. This tag can operate by harvesting and generating energy from Wi-Fi signal power. Wi-Fi device decodes information of the tag data by recognizing the power level of the backscattered Wi-Fi packets. Wi-Fi device receives the backscattered Wi-Fi packets and generates the tag's data pattern in the time-series of channel state information (CSI) values. We believe that this system can be achieved wireless connectivity for ultra- low-power IoT and wearable device.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.85-90
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• 2014

We realized a wireless multiple integrated laser engagement system composed of personal area network using Zigbee. The wireless laser detector had function of analog signal processor, decoder and wireless communication. However, it should consume low power and be small and light in order to be attached to a soldier's body. The decoder was realized in software to be small and light. We induced low power consumption as reducing the load of system using a narrow band optical filter. The fabricated wireless laser detector functioned well in optically noisy environment. Although the communication to the player unit through the wireless personal area network was dependent on the attachment place it was perfectly worked with transmission power of -40.2dBm or more.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.550-558
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• 2014

Direct Torque controlled induction motor (DTC-IM) drives use stator resistance of the motor for stator flux estimation. So, stator resistance estimation properly is very important for a stable and effective operation of the induction motor. Stator resistance variations because of changing in temperature make DTC operation difficult mainly at low speed. A method based on artificial neural network (ANN) to estimate the stator resistance online of IM for DTC drive is modeled and verified in this paper. To train the neural network a back propagation algorithm is used. Weight adjustment of neural network is done by back propagating the error signal between measured and estimated stator current. An extensive simulation has been carried out in MATLAB/SIMULINK to prove the efficacy of the proposed stator resistance estimator. The simulation & experimental result reveals that proposed method is able to obtain precise torque and flux control at low speed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.11
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• pp.2442-2450
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• 2010

Using sensor devices applied to various objects will be needed wireless network that it is easy to install in them. Tiny devices configured to processor that bas comparatively low computing ability are inappropriate to use devices that are wireless LAN, etc. In result, network devices needed to not only have simple communication protocol, but have Plug and Play function that it works as soon as it connects without installing any device driver. it also will industrially have both low power and low cost because of mobility of it. From IEEE 802.11 standard, WPAN(Wireless Personal Area Network) included in LAN is being developed by WPAN WG(Working Group) on area with low power consumption and low complexity. In addition to, it is standardizing MAC and PRY of the standard that is expected to wirelessly communicate within 10m. WPAN will be used generally in the more near future because of both low power and low cost of Zigbee. In this paper we designed zigbee based user authentication module for a automotive smart-key system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2469-2490
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• 2019

A low-energy adaptive clustering hierarchy (LEACH) protocol is a low-power adaptive cluster routing protocol which was proposed by MIT's Chandrakasan for sensor networks. In the LEACH protocol, the selection mode of cluster-head nodes is a random selection of cycles, which may result in uneven distribution of nodal energy and reduce the lifetime of the entire network. Hence, we propose a new selection method to enhance the lifetime of network, in this selection function, the energy consumed between nodes in the clusters and the power consumed by the transfer between the cluster head and the base station are considered at the same time. Meanwhile, the improved FTBA algorithm integrating the curve strategy is proposed to enhance local and global search capabilities. Then we combine the improved BA with LEACH, and use the intelligent algorithm to select the cluster head. Experiment results show that the improved BA has stronger optimization ability than other optimization algorithms, which the method we proposed (FTBA-TC-LEACH) is superior than the LEACH and LEACH with standard BA (SBA-LEACH). The FTBA-TC-LEACH can obviously reduce network energy consumption and enhance the lifetime of wireless sensor networks (WSNs).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.838-839
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• 2016

IEEE 802.15.4 is the standard wireless link technology for low power, low cost, but long lifetime applications including wireless sensor network (WSN). Currently, whether or not IP architecture should be used in WSN over its 802.15.4 link is under dispute. Such kind of arguments may last for a long time without some convincing experimental measurements of real case performances of IP over 802.15.4 implementation, and thus prevent the advance of related research. In RFC4944, IETF proposed the 6LoWPAN specification to enable IPv6 communication over low power, wireless personal area networks. We try to alleviate the dispute and make the direction clearer to the community so as to promote further valuable research in this topic.

• Journal of Sensor Science and Technology
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• v.29 no.1
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• pp.19-26
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• 2020

Electrocardiogram (ECG) classification has become an essential task of modern day wearable devices, and can be used to detect cardiovascular diseases. State-of-the-art Artificial Intelligence (AI)-based ECG classifiers have been designed using various artificial neural networks (ANNs). Despite their high accuracy, ANNs require significant computational resources and power. Herein, three different ANNs have been compared: multilayer perceptron (MLP), convolutional neural network (CNN), and spiking neural network (SNN) only for the ECG classification. The ANN model has been developed in Python and Theano, trained on a central processing unit (CPU) platform, and deployed on a PYNQ-Z2 FPGA board to validate the model using a Jupyter notebook. Meanwhile, the hardware accelerator is designed with Overlay, which is a hardware library on PYNQ. For classification, the MIT-BIH dataset obtained from the Physionet library is used. The resulting ANN system can accurately classify four ECG types: normal, atrial premature contraction, left bundle branch block, and premature ventricular contraction. The performance of the ECG classifier models is evaluated based on accuracy and power. Among the three AI algorithms, the SNN requires the lowest power consumption of 0.226 W on-chip, followed by MLP (1.677 W), and CNN (2.266 W). However, the highest accuracy is achieved by the CNN (95%), followed by MLP (76%) and SNN (90%).

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.4
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• pp.17-29
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• 1999

This paper presents a high level synthesis method targeting low power consumption for data-dominated CMOS circuits (e.g., DSP). The high level synthesis is divided into three basic tasks: scheduling, resource and register allocation. For lower power scheduling, we increase the possibility of reusing an input operand of functional units. For a scheduled data flow graph, a compatibility graph for register and resource allocation is formed, and then a special weighted network is then constructed from the compatibility graph and the minimum cost flow algorithm is performed on the network to obtain the minimum power consumption data path assignment. The formulated problem is then solved optimally in polynomial time. This method reduces both the switching activity and the capacitance in synthesized data path. Experimental results show 15% power reduction in benchmark circuits.