• The Journal of the Acoustical Society of Korea
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• v.22 no.7
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• pp.579-584
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• 2003

All of propagation path loss prediction models, which have been presented up to date, are oかy for ground living space. In reality, sea surface free space is different from ground living space in physical hierarchical structure. If the propagation path prediction model for ground living space is applied to the sea surface free space, propagation path loss will be smaller than actual value, while the maximum service straight line will become shorter. Thus this paper proposed and simulated the propagation path loss prediction model for predicting propagation path loss more accurately in sea surface free space, with its focus on CDMA mobile communication frequency band. Then the simulation results were compared to actual survey to verify its practicality.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.1 no.1
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• pp.35-39
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• 2008

In this paper, we have developed a propagation loss prediction software with GUI (Graphic User Interface) functions, based on the geometrical ray optics model, which can predict radio parameters for the deployment of wireless indoor network. The program has two numerical modules consisted with electrical image and ray launching methods to implement UTD theory. The simulated results are compared with reported data measured in the foreign building environments for office and '一' type corridor, and measured and simulated results for the propagation loss agree with each other quite well. Simulation results for '一' type corridor and 'T' type corridor propagation environment are shown for reference.

• ETRI Journal
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• v.15 no.3
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• pp.27-34
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• 1994

There have been traditional approaches to model radio propagation path loss mechanism both theoretically ad empirically. Theoretical approach is simple to explain and effective in certain cases. Empirical approach accommodates the terrain configuration and distance between base station and mobile unit along the propagation path only. In other words, it does not accommodate natural terrain configuration over a specific area. In this paper, we propose a spatial prediction technique for the mobile radio propagation path loss accommodating complete natural terrain configuration over a specific area. Statistical uncertainty analysis is also considered.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.7
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• pp.1398-1407
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• 1992

The prediction of heat loss during laminar flame propagation was carried out by measurement of gas pressure and visualization of flame propagation in the constant volume combustion chamber. And to validate the prediction, the instantaneous temperature at wall of combustion chamber was also measured. Consequently, it was found that heat loss was increased according to increasing of maximum flame travel distance, but rate of heat loss for heat release during laminar flame propagation was nearly constant. And heat loss depends on heat transfer area which was contacted the wall by burned gas regardless to spark plug location.

• Journal of KIISE:Software and Applications
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• v.26 no.10
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• pp.1143-1155
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• 1999

셀룰러 방식의 이동통신 시스템에서 전파의 유효신호 도달범위를 예측하기 위해서는 전파전파 모델을 이용한 예측기법이 주로 사용된다. 그러나, 전파과정에서 주변 지형지물에 의해 발생하는 전파손실은 매우 복잡한 비선형적인 특성을 가지며 수식으로는 정확한 표현이 불가능하다. 본 논문에서는 신경회로망의 함수 근사화 능력을 이용하여 전파손실 예측모델을 생성하는 방법을 제안한다. 즉, 전파손실을 송수신 안테나간의 거리, 송신안테나의 특성, 장애물 투과영향, 회절특성, 도로, 수면에 의한 영향 등과 같은 전파환경 변수들의 함수로 가정하고, 신경회로망 학습을 통하여 함수를 근사화한다. 전파환경 변수들이 신경회로망 입력으로 사용되기 위해서는 3차원 지형도와 벡터지도를 이용하여 전파의 반사, 회절, 산란 등의 물리적인 특성이 고려된 특징 추출을 통해 정량적인 수치들을 계산한다. 이와 같이 얻어진 훈련데이타를 이용한 신경회로망 학습을 통해 전파손실 모델을 완성한다. 이 모델을 이용하여 서울 도심 지역의 실제 서비스 환경에 대한 타 모델과의 비교실험결과를 통해 제안하는 모델의 우수성을 보인다.Abstract In cellular mobile communication systems, wave propagation models are used in most cases to predict cell coverage. The amount of propagation loss induced by the obstacles in the propagation path, however, is a highly non-linear function, which cannot be easily represented mathematically. In this paper, we introduce the method of producing propagation loss prediction models by function approximation using neural networks. In this method, we assume the propagation loss is a function of the relevant parameters such as the distance from the base station antenna, the specification of the transmitter antenna, obstacle profile, diffraction effect, road, and water effect. The values of these parameters are produced from the field measurement data, 3D digital terrain maps, and vector maps as its inputs by a feature extraction process, which takes into account the physical characteristics of electromagnetic waves such as reflection, diffraction and scattering. The values produced are used as the input to the neural network, which are then trained to become the propagation loss prediction model. In the experimental study, we obtain a considerable amount of improvement over COST-231 model in the prediction accuracy using this model.

• ETRI Journal
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• v.28 no.2
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• pp.247-249
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• 2006

In the development of a new wireless communications system, a versatile and accurate radio channel for indoor communications is needed. In particular, the investigation of radio transmission into buildings is very important. In this letter, we present an improved three-dimensional electromagnetic wave propagation prediction model for indoor wireless communications that takes into consideration building penetration loss. A ray tracing technique based on an image method is also employed in this study. Three-dimensional models can predict any complex indoor environment composed of arbitrarily shaped walls. A speed-up algorithm, which is a modified deterministic ray tube method, is also introduced for efficient prediction and computation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.3
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• pp.419-429
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• 1999

Identifying the boundary of the effective receiving power of waves is one of the most important factors for cell optimization. In this paper, we introduce a propagation loss prediction model which yields highly accurate prediction in very complex areas as Seoul where a mixture of many large buildings, small buildings, broad streets, narrow alleys, rivers and forests co-exist in an irregular arrangement. This prediction model is based on neural networks trained on field measurement data collected in the past. Using these data along with 3-D digital elevation maps and vector data for building structures, we extract the parameter values which mainly affect the amount of propagation loss. These parameter values are then used as the inputs to the neural network. Trained neural network becomes the approximated function of the propagation loss model which generalizes very well and can predict accurately in the regions not included in training the neural network. The experimental results show a superior performance over the other models in the cells operating in the city of Seoul.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.11
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• pp.1-8
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• 1997

A prediction model is proposed to describe the path loss in propagation environment of indoor microcell. This model includes the lineal corridor for line--of-sight(LOS) and T-shaped corridor for non-line-of-sight(NLOS). In computation of receiving power the ray tracing technique based on image method is utilized and also reflected waves bounced on the walls and ceilings are considered. To check validity of the computed resuls cross checks between the predicted and measured are being made, which shows a close agreement for LOS case whereas somewhat disagreement for NLOS case. UTD technique is incorporated with propagation path determination algorithm in the treatment of NLOS case.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.7
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• pp.47-54
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• 1994

The propagation prediction within a cell coverage in land mobile radio service is very important. The propagation loss is presented in a A+B logS110TR form, where both A and B are the parameter as function of the frequency and the antenna height and R is the distance of between base and mobile station. The propagation prediction is Cheju area is not easy, because a great number of peaks are found here and there at the foot of the Hanla Mt. The characteristics of radio propagation in Cheju area are measured for the Seorum transmitter site. The formular of correction which is regard to the configuration of the ground is presented, and the predicted values are compared with the measured one.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1796-1802
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• 2011

In this paper, the radio propagation path loss prediction simulator in tunnel was developed. It used a image theory method for analysing precise radio propagation path. And it can predict radio propagation path loss in straight and curved tunnels. The simulator can plot realtime radio propagation paths using various parameters which was input by user. And it can simulate from changing transmitter and receiver positions. The predicted path loss of simulator was compared with the measurements in Chunhyun tunnel and confirmed the validity.