• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.2
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• pp.53-61
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• 2017

How to manage manhole is to estimate the part without observation and maintain the sewer. To get the information about current flow rate, visiting and measuring specific manhole is positively necessary. Also, there are some problems that accurate measurement of flow rate is difficult and obtaining the information about real-time whole flow rate is impossible. This thesis will easily grasp the accurate location and type of manhole to solve the problems, and provide the manhole system conveying information through direct radio communication with a manhole cover to renewal information of manhole properly. Besides, it intends to save the information about management of waterworks, maintenance of facilities, data for flow rate, and structure of manhole. Using these, it is supposed to offer how to handle manhole. Thus, this thesis delivers the information to manhole and into central servers directly without wire and provides the system and management method for effective maintenance of manhole.

• Journal of Integrative Natural Science
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• v.14 no.2
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• pp.50-56
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• 2021

Due to the recent increase in the mobile streaming market, mobile traffic is increasing exponentially. IMT-2020, named as the next generation mobile communication standard by ITU, is called the 5th generation mobile communication (5G), and is a technology that satisfies the data traffic capacity, low latency, high energy efficiency, and economic efficiency compared to the existing LTE (Long Term Evolution) system. 5G implements this technology by utilizing a high frequency band, but there is a problem of path loss due to the use of a high frequency band, which is greatly affected by system performance. In this paper, small cell technology was presented as a solution to the high frequency utilization of 5G mobile communication system, and furthermore, the system performance was improved by applying machine learning technology to macro communication and small cell communication method decision. It was found that the system performance was improved due to the technical application and the application of machine learning techniques.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.36-37
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• 2022

선박의 안천한 항해를 돕기 위하여 해상에 항로표지를 설치하여 운영하고 있다. 해상 ICT(Information and Communications Technology)의 발달로 AtoN AIS(Automatic Identification System) 및 CDMA(Code Division Multiple Access), LTE(Long Term Evolution) 등 다중통신망을 이용하여 항로표지의 상태를 감시하고 제어가 가능해짐에 따라 해양수산부에서는 항로표지 관리운영시스템을 운영하고 있다. e-Navigation 및 자율운항선박 분야 등에 항로표지 스마트화를 위해 정확한 항로표지 정보가 요구된다. 본 논문에서는 정확한 항로표지 정보 제공을 위해 관리운영시스템 표준소프트웨어 문제점을 분석하고 개선방안에 대해서 소개한다.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.3-9
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• 2017

Recently, in 3rd Generation Partnership Project(3GPP), there is a study of the Long Term Evolution(LTE) based vehicle communication which has been actively conducted to provide a transport efficiency, telematics and infortainment. Because the vehicle communication is closely related to the safety, it requires a reliable communication. Because vehicle speed is very fast, unlike the movement of the user, radio channel is rapidly changed and generate a number of problems such as transmission quality degradation. Therefore, we have to continuously updates the channel estimates. There are five types of conventional channel estimation scheme. Least Square(LS) is obtained by pilot symbol which is known to transmitter and receiver. Decision Directed Channel Estimation(DDCE) scheme uses the data signal for channel estimation. Constructed Data Pilot(CDP) scheme uses the correlation characteristic between adjacent two data symbols. Spectral Temporal Averaging(STA) scheme uses the frequency-time domain average of the channel. Smoothing scheme reduces the peak error value of data decision. In this paper, we propose the novel channel estimation scheme in LTE based Vehicle-to-Vehicle(V2V) environment. In our Hybrid Reliable Channel Estimation(HRCE) scheme, DDCE and Smoothing schemes are combined and finally the Linear Minimum Mean Square Error(LMMSE) scheme is applied to minimize the channel estimation error. Therefore it is possible to detect the reliable data. In simulation results, overall performance can be improved in terms of Normalized Mean Square Error(NMSE) and Bit Error Rate(BER).

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.7
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• pp.602-609
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• 2018

This paper proposes the hybrid crypto-system for fast video data encryption of UAV(Unmanned Aerial Vehicle) under the LTE(Long-Term Evolution) wireless communication environment. This hybrid crypto-system is consisted of ECC(Elliptic Curve Cryptography) public key algorithm and LEA(Light-weight Encryption Algorithm) symmetric key algorithm. ECC is a faster public key algorithm with the same security strength than RSA(Rivest Shamir Adleman), and Korean standard LEA with the same key size is also a faster symmetric key algorithm than AES(Advances Encryption Standard). We have implemented this hybrid crypto-system using OpenSSL, OpenCV and Socket programs under the Swarm 8-UAV. We have shown the efficient adaptability of this hybrid crypto-system for the real-time swarm UAV through the experiments under the LTE communication environment.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.9
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• pp.895-902
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• 2014

This paper presents a 2-stage CMOS power amplifier for the 1.75 GHz band using a $0.18-{\mu}m$ CMOS process. Using ADS simulation, a power gain of 28 dB and an efficiency of 45 % at an 1dB compression point of 27 dBm were achieved. The implemented CMOS power amplifier delivered an output power of up to 24.8 dBm with a power-added efficiency of 41.3 % and a power gain of 22.9 dB. For a 16-QAM uplink LTE signal, the PA exhibited a power gain of 22.6 dB and an average output power of 23.1 dBm with a PAE of 35.1 % while meeting an ACLR(Adjacent Channel Leakage Ratio) level of -30 dBc.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.10
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• pp.898-907
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• 2013

For D2D communications underlaying cellular networks, it is essential to consider the mutual interference between the existing cellular communications and D2D communications as well as the spectral efficiency, as they need to share the same frequency. Accordingly, a resource allocation scheme should be designed in such a way that minimizes the mutual interference and maximizes the spectrum utilization efficiency at the same time. In this paper, we propose a resource allocation scheme based on cooperation of the base station and D2D terminals. Specifically, a D2D terminal senses the cellular spectrum to recognize the interference condition, chooses the best cellular resource, and reports the information to the base station. The base station allocates D2D resource such that the corresponding D2D link and cellular link share the same resource. The performance of the proposed resource allocation scheme is ated through compu under 3GPP LTE-Advanced scenarios.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.8-19
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• 2019

Since their emergence in 2007, smart phones have advanced up to the point that 5G mobile communication in 2019 started to be commercialized. Accordingly, now it is possible to share 3D modeling files and collaborate by means of a mobile web. As the recently commercialized 5G mobile communication network is so useful in sharing 3D modeling files and collaborating that even large-size geometry files can be transmitted at ultra high speed with ultra low transfer delay. We examines characteristics of major 3D file formats such as STL, OBJ, FBX, and glTF and compares the existing 4G LTE (Long Term Evolution) network with the 5G NR (New Radio) mobile communication network. The loading time and packets of each format were measured depending on the mobile web browser environments. We shows that in comparison with 4G LTE, the loading time of STL and OBJ file formats were reduced as much as 6.55 sec and 9.41 sec, respectively in the 5G NR and Chrome browsers. The glTF file format showed the most efficient performance in all of the 4G/5G mobile communication networks, Chrome, and Edge browsers. In the case of STL and OBJ, the traffic was relatively excessive in 5G NR and Edge browsers. The findings of this study are expected to be utilized to develop a 3D file format that reduces the loading time in a mobile web environment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.2
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• pp.213-224
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• 2012

The integrated core network architecture and various mobile subscriber behavior can result in a significant increase of signaling load inside the evolved packet core network proposed by 3GPP in Release 8. Consequently, an authentication signaling analysis can provide insights into reducing the authentication signaling loads and latency, satisfying the quality-of-experience. In this paper, we evaluate the signaling loads in the EPS architecture via analytical modeling based on the renewal process theory. The renewal process theory works well, irrespective of a specific random process (i.e. Poisson). This paper considers various subscribers patterns in terms of call arrival rate, mobility, subscriber's preference and operational policy. Numerical results are illustrated to show the interactions between the parameters and the performance metrics. The sensitivity of vertical handover performance and the effects of heavy-tail process are also discussed.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.3
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• pp.217-227
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• 2022

In order to provide a location-based services regardless of indoor or outdoor space, it is important to provide position information of the terminal regardless of location. Among the wireless/mobile communication resources used for this purpose, Long Term Evolution (LTE) signal is a representative infrastructure that can overcome spatial limitations, but the positioning method based on the location of the base station has a disadvantage in that the accuracy is low. Therefore, a fingerprinting technique, which is a pattern recognition technology, has been widely used. The simplest yet widely applied algorithm among Fingerprint positioning technologies is k-Nearest Neighbors (kNN). However, in the kNN algorithm, it is difficult to find the optimal K value with the lowest positioning error for each location to be estimated, so it is generally fixed to an appropriate K value and used. Since the optimal K value cannot be applied to each estimated location, therefore, there is a problem in that the accuracy of the overall estimated location information is lowered. Considering this problem, this paper proposes a technique for adaptively varying the K value by using a Convolutional Neural Network (CNN) model among Artificial Neural Network (ANN) techniques. First, by using the signal information of the measured values obtained in the service area, an image is created according to the Physical Cell Identity (PCI) and Band combination, and an answer label for supervised learning is created. Then, the structure of the CNN is modeled to classify K values through the image information of the measurements. The performance of the proposed technique is verified based on actual data measured in the testbed. As a result, it can be seen that the proposed technique improves the positioning performance compared to using a fixed K value.