• 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 the Korea institute of electronic communication sciences
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• v.6 no.2
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• pp.157-162
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• 2011

International Telecommunication Union(ITU), recommended a propagation prediction models that can be applied to a various propagation environments that many services have been established in the field of broadcasting and telecommunications using ITU-R. Each propagation prediction models are revised with the complement procedures of an expected difference of channel environment and prepared for a standard of a propagation prediction. In this research, it is possible to realized a practical propagation prediction in each transmitting station for a broadcasting environments of ITU-R Rec. P.1546-3 model, so called the point-to-area, using supplementary parameters of the transmitting station specification.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12A
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• pp.1883-1890
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• 1999

Wireless communication in an urban area, the accurate prediction of wave propagation characteristics are very important to determine communication service areas, select optimal base-stations, and design cells, etc. The CCIR model is a propagation prediction model using a shadowing by the buildings in an urban area. This model represent the shadowing rate by the means of the effect of shadowing between base-station and mobile unit in a shaped linear plane. But, This one occurred a lot of prediction error because it did not consider that density area by the buildings and terrain configurations by the hill and mountain on Line-Of-Sight. In this thesis, an improved propagation prediction model is proposed to reduce prediction error. We presents a new equation, which is using the SAS. This equation is associated with the shadow height by the buildings that considers the topology and the number of blocks that can affect the building shadow in the Line-Of-Sight. We measure the received electrical field level of base-station that high density area, medium density area, and low density area, and then compare and analysis the result to prediction of CCIR model and proposed model. The result compared with the measurement, the proposed model has the improvement of 9.71dB in a high density area, 9.66dB in a medium density area, and 4.02dB in a low density area better than the CCIR model. The result compared with the measurement, the proposed model has the improvement of 9.71dB in a high density area, 9.66dB in a medium density area, and 4.02dB in a low density area better than the CCIR model.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.3
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• pp.69-80
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• 1993

It is important to prevent roll failure in hot rolling process for reducing maintenance coat and production loss. Roll material and rolling conditions such as the roll force and torque have been intensively investigated to overcome the roll failures. In this study, a computer roll life prediction system under working condition is developed and evaluated on IBM-PC level. The system is composed and fatigue estimation models which are stress analysis, crack propagation, wear and fatigue estimation. Roll damage can be predicted by calculating the stress anplification, crack depth propagation and fatigue level in the roll using this computer model. The developed system is applied to a work roll in actual hot rolling process for reliability evaluation. Roll failures can be diagnosed and the propriety of current working condition can be determined through roll life prediction simulation.

• The Journal of the Acoustical Society of Korea
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• v.16 no.4
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• pp.49-56
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• 1997

In mobile communications, it is very important that we predict the propagation environments of radiation pattern, in order to decide the service area, select the best location of the best station, design the cell etc. Therefore, by analyzing the propagation prediction model that is varied according to the kind of antenna, the beam angle, the terrain and obstacles, we expect that the economic operating of communication networks, the calling quality and the service of subscriber will be enhanced. In this paper, we select the around of Seji base station in Naju-city Chonnam for modern suburban area and measure the field strength to propose the optimal propagation prediction model for suburban areas. We propose the propagation prediction model that, it is not found in the other models until now, consists of the correction coefficient with the relative differences of antenna effective height of the base station and mobile station for minimizing errors. Finally, comparing the results of the field test with the computer simulation(PPGIS : Propagation Prediction Geographic Information System) results for the Hata model, the Egri model, the Carey model and the propose model, we confirm the property of the proposed model.

• The Journal of the Acoustical Society of Korea
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• v.18 no.8
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• pp.100-107
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• 1999

When a subscriber service composed along the central street of urban in microcell and picocell mobile communication of cellular method, we proposed the propagation prediction model that mobile communication environment of urban can analyze exactly and faster men than a precedent. We simulate the proposed propagation prediction model under the urban propagation environment of PCS mobile communication and analyze distribution of received field strength in cell. As a results, we show the optimal condition of the transmitting power and the position of the base station in the microcell and the picocell mobile communication.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.2
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• pp.200-206
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• 2008

To implement a mobile radio system, wave-propagation models are necessary to determine propagation characteristics accurately, Currently, the empirical/theoretical prediction models for urban environments are fairly well-developed. But there is a lack of a suitable prediction model for mountain region. So in this paper, to develop the prediction model for mountain region, propagation environments are classified based on three basic mechanisms: reflection, diffraction, penetration(absorbtion and scattering), and measurements have been performed for the classified mountain regions including open area, forest and ridge. Using the measurement data, empirical modeling of propagation characteristics are performed, and then a prediction model for mountain region is proposed.

• The Journal of the Korea Contents Association
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• v.4 no.2
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• pp.21-27
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• 2004

In an urban area telecommunication using wireless system, the accurate prediction and analysis of wave propagation characteristics are very important to determine the service area optimized selection of base station, and eel design, etc. In the stage of these analyses, we have to present the propagation prediction mood which is varied with the type of antenna, directional angle, and configuration of the ground in our urban area in addition we need to perform an analysis of the conventional mode which is similar to ours and dig out the parameters to evaluate the wave environment before the cell design for the selected area. In this paper, we propose a wave propagation prediction model concerning the topography and obstacles in our urban area. We extract the parameters and apply them to the proposed wave environment for the simulation analyzing the propagation characteristics. Throughout these analyzing procedure, we extracted the essential parameters such as the position of the base station, the height of topography, and adequate type and height of the antenna with our preferable cuteness.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1865-1869
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• 2004

A new model for the propagation prediction for mobile communication network inside building is presented in this paper. The model is based on the determination of the dominant paths between the transmitter and the receiver. The field strength is predicted with adaptive neuro - fuzzy inference systems (ANFIS), trained with measurements. The advantage of the ANFIS with hybrid least squares and gradient descent algorithms is fast convergence compared with original neural network. The K-means algorithm for selection of training patterns is also used. Comparison of our predicted results to measurements indicate that improvements in accuracy over conventional empirical model are achieved.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.1
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• pp.133-141
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• 1999

In this paper, we present an indoor propagation prediction model which is based on a three-dimensional ray-tracing technique. In this model, instead of considering all obstacles such as furnitures and fixtures, etc., only main obstacles to the propagation such as walls, ceiling and floors are modeled as slabs with finite thickness and conductivity, and the significant phenomena of propagation are considered, so we can calculate simply and predict accurately the propagation losses. The propagating rays are considered to be reflected and transmitted specularly at the boundaries of obstacles, and diffracted at edges. The reflection and transmission losses on flat obstacles are calculated by using ray tracing method, and the diffraction losses at edges are calculated by using the uniform theory of diffraction (UTD) for finite conductivity media. The results simulated for some cases by this propagation model good agree with the measured value of pathloss.