• 한국전자파학회논문지
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• 제12권5호
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• pp.772-772
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• 2001

본 논문에서는 영상법 기반의 3차원 광선추적법에 패치산란모델을 이용하여 실내 구조물을 고려할 수 있는 실내 전파모델링 방법을 제시하였다. 실내 구조물을 모델링하기 위한 패치산란모델은 패치형태의 직사각형 평면에 대한 RCS를 이용하여 입사에 대한 산란현상을 정의한 것으로써, 책상이나 테이블 같은 평면적인 실내구조물에 대한 산란현상을 각각의 구조물에 대한 영상 안테나를 발생시키는 복잡한 과정 없이 간단하게 해석하기 위한 것이다. RCS는 간단히 입사 전력에 대한 산란 전력의 비로 정의되며 본 논문에서는 다양한 수신 각도에서 바라보는 bistatic RCS를 물리광학(Physical Optics)을 이용하여 수식적으로 유도하여 패치산란모델에 이용하였다. 또한 실내의 다중경로 성분에 대해 계산하지 않는 패치산란모델을 실내에 적용하기 위하여 복잡한 수식보다는 단순한 보정값인 실내보정값을 정의하였는데, 본 논문에서는 이 값을 다양한 패치 환경의 측정에 의한 경험적 상수로 처리함으로써 RCS의 고려만으로는 실내에 적용할 수 없는 점을 극복하였다.

• 한국전자파학회논문지
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• 제12권5호
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• pp.722-733
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• 2001

본 논문에서는 영상법 기반의 3차원 광선추적법에 패치산란모델을 이용하여 실내 구조물을 고려할 수 있는 실내 전파모델링 방법을 제시하였다. 실내 구조물을 모델링하기 위한 패치산란모델은 패치형태의 직사각형 평면에 대한 RCS를 이용하여 입사에 대한 산란현상을 정의한 것으로써, 책상이나 테이블 같은 평면적인 실내구조물에 대한 산란현상을 각각의 구조물에 대한 영상 안테나를 발생시키는 복잡한 과정 없이 간단하게 해석하기 위한 것이다. RCS는 간단히 입사 전력에 대한 산란 전력의 비로 정의되며 본 논문에서는 다양한 수신 각도에서 바라보는 bistatic RCS를 물리광학(Physical Optics)을 이용하여 수식적으로 유도하여 패치산란모델에 이용하였다. 또한 실내의 다중경로 성분에 대해 계산하지 않는 패치산란모델을 실내에 적용하기 위하여 복잡한 수식보다는 단순한 보정값인 실내보정값을 정의하였는데, 본 논문에서는 이 값을 다양한 패치 환경의 측정에 의한 경험적 상수로 처리함으로써 RCS의 고려만으로는 실내에 적용할 수 없는 점을 극복하였다.

• 한국환경보건학회지
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• 제32권4호
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• pp.268-274
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• 2006

In this study in order to evaluate the growth of RF propagation exposure rate generated according to the enhancement of its use, it is proposed for the ground to be able to examine and to contemplate the correlation between the human health and RF propagation exposure rate by measuring and analyzing the RF exposure source and exposure rate in an indoor environment. As a result of research, it is analyzed that the main exposure source of critically making effect in indoor environment is the frequency hand if radio broadcasting, mobile communication, wireless LAN, digital broadcasting, home appliance, etc., including the TV broadcasting. Among these, it is shown that the TV broadcasting and mobile communication band are the highest. And it is the concluded that RF exposure rate of the environmental sensitive equipment, like an institution for the aged, has lower possibility to exceed the human RF protection criteria by this evaluation.

• 한국정보통신학회논문지
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• 제7권5호
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• pp.872-878
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• 2003

본 논문에서는 3D-Ray Tracing 기법을 이용한 옥내 무선통신용 편파발생 시뮬레이터를 개발하고, 실내 무선전파환경에서 실제 측정한 데이터와의 비교를 통하여 검증하였다. 개발된 시뮬레이터를 이용하여 Line-Of-Sight(LOS)와 Non-Line-Of-Sight(NLOS) 무선전파 환경에서 수직, 수평, 원편파에 대한 채널특성과 편파 다이버시티 수신특성을 해석하였다. 그 결과 원편파의 경우 기수회 반사파를 억제 수신하는 특성 때문에 수직 및 수평편파의 경우와 비교하여 다중경로 페이딩이 현저하게 경감됨을 알 수 있었다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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• pp.865-868
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• 1999

In this paper, indoor propagation characteristics are analyzed for various environments such as corridors, walls and corners. In order to present the statistical model for indoor environments the loss factors of each case are obtained by linear regression analysis method with the function of logarithmic distance between transmitter and receiver.

• ETRI Journal
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• 제42권1호
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• pp.7-16
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• 2020

Assuming omnidirectional antenna reception, the ITU-R recently developed a new propagation model on building entry loss (BEL) for 5G millimeter-wave frequency sharing and compatibility studies, which is a simplified outdoor-to-indoor path loss model. Considering the utilization of high-gain narrow-beamwidth beamforming, the omnidirectional-based ITU-R BEL model may not be appropriate to predict propagation characteristics for directional beamforming scenarios. This paper studies the effects of beamwidth on the ITU-R BEL model. This study is based on field measurements collected with four different beamwidth antennas: omnidirectional, 10° horn, 30° horn, and 60° horn. The measurement campaigns were conducted at two types of building sites: traditional and thermally efficient buildings. These sites, as well as the measurement scenarios, were carefully chosen to comply with the ITU-R BEL measurement guidelines and the ITU-R building types. We observed the importance of accurate beam alignment from the BEL variation range. We were able to quantify the beamwidth dependency by fitting to a model that is inversely proportional to the beamwidth.

• Architectural research
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• 제8권1호
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• pp.37-45
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• 2006

A fungal spore transportation model that accounts for the concentration of airborne indoor spores and the amount of spores deposited on interior surfaces has been developed by extending the current aerosol model. This model is intended to be used for a building with a mechanical ventilation system, and considers HVAC filter efficiency and ventilation rate. The model also includes a surface-cleaning efficiency and frequency that removes a portion of spores deposited on surfaces. The developed model predicts indoor fungal spore concentration and provides an indoor/outdoor ratio that may increase or decrease mold growth risks in real, in-use building cases. To get a more useful outcome from the model simulation, an uncertainty analysis has been conducted in a real building case. By including uncertainties associated with the parameters in the spore transportation model, the simulation results provide probable ranges of indoor concentration and indoor/outdoor ratio. This paper describes the uncertainty quantification of each parameter that is specific to fungal spores, and uncertainty propagation using an appropriate statistical technique. The outcome of the uncertainty analysis showed an agreement with the results from the field measurement with air sampling in a real building.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2016년도 추계학술발표대회
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• pp.168-171
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• 2016

In recent years, indoor localization in Wi-Fi environment has been researched for its location determining capability. The fingerprint and RF propagation models has been the main approach in determining indoor positioning. With the use of fingerprint, a low-cost, versatile localization system can be achieved without the use of external hardware. However, only a few research have been made on virtual access points (VAPs) among indoor localization models. In this paper, the idea of indoor localization system using fingerprint with the addition of VAP in Wi-Fi environment is discussed. The idea is to virtually add APs in the existing indoor Wi-Fi system, this would mean additional virtually APs in the network. The experiments of the proposed algorithm shows the positive results when 2VAPs are used compared with only APs. A combination of 3APs and 2VAPs had the lowest average error in all 4 scenarios with 3.99 meters.

• 전기전자학회논문지
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• 제26권2호
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• pp.186-195
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• 2022

In this paper, we propose a new algorithm to improve the accuracy of indoor positioning techniques using Wi-Fi access points as beacon nodes. The proposed algorithm is based on the Weighted Centroid algorithm, a popular method widely used for indoor positioning, however, it improves some disadvantages of the Weighted Centroid method and also for other kinds of indoor positioning methods, by using the received signal strength correction method and genetic algorithm to prevent the signal strength fluctuation phenomenon, which is caused by the complex propagation environment. To validate the performance of the proposed algorithm, we conducted experiments in a complex indoor environment, and collect a list of Wi-Fi signal strength data from several access points around the standing user location. By utilizing this kind of algorithm, we can obtain a high accuracy positioning system, which can be used in any building environment with an available Wi-Fi access point setup as a beacon node.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2020년도 하계학술대회
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• pp.717-720
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• 2020

An indoor localization system that uses Wi-Fi RSSI signals for localization gives accurate user position results. The conventional Wi-Fi RSSI signal based localization system uses raw RSSI signals from access points (APs) to estimate the user position. However, the RSSI values of a particular location are usually not stable due to the signal propagation in the indoor environments. To reduce the RSSI signal fluctuations, shadow fading, multipath effects and the blockage of Wi-Fi RSSI signals, we propose a Wi-Fi localization system that utilizes the advantages of Wi-Fi RSSI heat maps. The proposed localization system uses a regression model with deep convolutional neural networks (DCNNs) and gives accurate user position results for indoor localization. The experiment results demonstrate the superior performance of the proposed localization system for indoor localization.