• Journal of Korea Society of Industrial Information Systems
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• v.17 no.2
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• pp.19-27
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• 2012

In railway tunnel environment, the reliability of a high-data-rate and real-time train-to-wayside communication should be maintained especially when high-speed train moves along the track. In China and Europe, the communication frequency around 900 MHz is widely used for railway applications. At this carrier frequency band, both of the solutions based on continuously laid leaky coaxial cable (LCX) and discretely installed base-station antennas (BSAs), are applied in tunnel radio coverage. Many available works have concentrated on the radio-wave propagation in tunnels by different kinds of prediction models. Most of them solve this problem as natural propagation in a relatively large hollow waveguide, by neglecting the transmitting/receiving (Tx/Rx) components. However, within such confined areas like railway tunnels especially loaded with train, the complex communication environment becomes an important factor that would affect the quality of the signal transmission. This paper will apply a full-wave numerical method to this case, for considering the BSA or LCX, train antennas and their interacted environments, such as the locomotive body, overhead line for power supply, locomotive pantograph, steel rails, ballastless track, tunnel walls, etc.. Involving finite-difference time-domain (FDTD) method and uni-axial anisotropic perfectly matched layer (UPML) technique, the entire wireless RF downlinks of BSA and LCX to tunnel space to train antenna are precisely modeled (so-called integrative modeling technique, IMT). When exciting the BSA and LCX separately, the field distributions of some cross-sections in a rectangular tunnel are presented. It can be found that the influence of the locomotive body and other tunnel environments is very significant. The field coverage on the locomotive roof plane where the train antennas mounted, seems more homogenous when the side-laying position of the BSA or LCX is much higher. Also, much smoother field coverage solution is achieved by choosing LCX for its characteristic of more homogenous electromagnetic wave radiation.

• Proceedings of the KSR Conference
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• 2006.11b
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• pp.1454-1460
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• 2006

This paper assesses communication performance using a roaming simulator when roaming occurs between onboard and ground wireless communication devices for communication based train control system (CBTC). Generally, CBTC is defined as the system regularly collecting location and speed data from each train, transmitting distance information to a train, and optimizing train speed according to train performance. When a train is moving, roaming is also performed to continuously transmit and receive train control information between the ground controller and the train. To operate CBTC, packet loss rate should be less than 1%, roaming time less than 100ms during roaming. We developed a roaming simulator to check communication performance before installing ground and onboard equipments on actual wireless sections. The roaming simulator to be introduced in this paper is for roaming simulation before conducting CBTC field test, which is the project to develop Urban Rail Signaling System Standards, being conducted in KRRI. The simulation consists of one onboard wireless communication device and three ground wireless communication devices, and the roaming simulator estimate packet loss rate occurring during roaming process of the two devices. Therefore, if you use the roaming simulator before the field test, you can predict various problems to occur in actual environment and reduce time, cost and people necessary to resolve these problems.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.38 no.12
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• pp.1-9
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• 2001

In the APON(ATM Passive Optical Network), the transmission of the upstream traffic is based on a TDMA(Time Division Multiple Access) method that an OLT(Optical Line Termination) permits ONUs(Optical Network Units) sending cells by allocating time slots. Because the upstream is not a streaming mode, the cell synchronizer has to be operated in the burst mode. Also, the cell phase monitor is required to prevent collisions between cells which are transmitted by multiple ONUs through a single optical fiber. In this paper, a TDMA burst cell synchroniser is implemented with the FPGA(Field Programmable Gate Array) being used in the APON based on G.983.1 for transmitting upstream cells. It has two main functions which are the upstream data recovery and the phase monitoring. The former is to recover the upstream data and clock in the OLT by seeking the preamble which is the overhead of the upstream time slot and by aligning the phase of the bit and cell with the system clock. The latter is to provide the information to the ONU to compensate for the equalization delay by monitoring continuously the phase difference between adjacent cells to avoid the cell collision on the upstream.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.4
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• pp.418-425
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• 2014

This paper presents a Ku-Band Doppler Radar System to measure respiration and heart rate. It was measured by using simultaneous radar and ECG(Electrocardiogram). Arctangent demodulation without dc offset compensation can be applied to transmitted I/Q(In-phase & Quadrature-phase) signal in order to improve the RMSE(Root Mean Square Error) about 50 %. The power leaked to receiving antenna from the transmitting antenna is always generated because of continuously opening the transceiver of CW(Continuous Wave) Doppler radar. As the output power increase, leakage power has an effect on the SNR(Signal-to-Noise Ratio) of the system. Therefore, in this paper, leakage cancellation technique that adds the signal having the opposite phase of the leakage power to the leakage power was implemented in order to minimize the decline of receiver sensitivity. By applying the leakage cancellation techniques described above, it is possible to measure the heart rate and respiration of the human at a distance of up to 35 m. the heart rate of the measured data at a distance of 35 m accords with the heart rate extracted from the ECG data.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.109-122
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• 2016

Recently, big data analysis has developed into a field of interest to individuals and non-experts as well as companies and professionals. Accordingly, it is utilized for marketing and social problem solving by analyzing the data currently opened or collected directly. In Korea, various companies and individuals are challenging big data analysis, but it is difficult from the initial stage of analysis due to limitation of big data disclosure and collection difficulties. Nowadays, the system improvement for big data activation and big data disclosure services are variously carried out in Korea and abroad, and services for opening public data such as domestic government 3.0 (data.go.kr) are mainly implemented. In addition to the efforts made by the government, services that share data held by corporations or individuals are running, but it is difficult to find useful data because of the lack of shared data. In addition, big data traffic problems can occur because it is necessary to download and examine the entire data in order to grasp the attributes and simple information about the shared data. Therefore, We need for a new system for big data processing and utilization. First, big data pre-analysis technology is needed as a way to solve big data sharing problem. Pre-analysis is a concept proposed in this paper in order to solve the problem of sharing big data, and it means to provide users with the results generated by pre-analyzing the data in advance. Through preliminary analysis, it is possible to improve the usability of big data by providing information that can grasp the properties and characteristics of big data when the data user searches for big data. In addition, by sharing the summary data or sample data generated through the pre-analysis, it is possible to solve the security problem that may occur when the original data is disclosed, thereby enabling the big data sharing between the data provider and the data user. Second, it is necessary to quickly generate appropriate preprocessing results according to the level of disclosure or network status of raw data and to provide the results to users through big data distribution processing using spark. Third, in order to solve the problem of big traffic, the system monitors the traffic of the network in real time. When preprocessing the data requested by the user, preprocessing to a size available in the current network and transmitting it to the user is required so that no big traffic occurs. In this paper, we present various data sizes according to the level of disclosure through pre - analysis. This method is expected to show a low traffic volume when compared with the conventional method of sharing only raw data in a large number of systems. In this paper, we describe how to solve problems that occur when big data is released and used, and to help facilitate sharing and analysis. The client-server model uses SPARK for fast analysis and processing of user requests. Server Agent and a Client Agent, each of which is deployed on the Server and Client side. The Server Agent is a necessary agent for the data provider and performs preliminary analysis of big data to generate Data Descriptor with information of Sample Data, Summary Data, and Raw Data. In addition, it performs fast and efficient big data preprocessing through big data distribution processing and continuously monitors network traffic. The Client Agent is an agent placed on the data user side. It can search the big data through the Data Descriptor which is the result of the pre-analysis and can quickly search the data. The desired data can be requested from the server to download the big data according to the level of disclosure. It separates the Server Agent and the client agent when the data provider publishes the data for data to be used by the user. In particular, we focus on the Big Data Sharing, Distributed Big Data Processing, Big Traffic problem, and construct the detailed module of the client - server model and present the design method of each module. The system designed on the basis of the proposed model, the user who acquires the data analyzes the data in the desired direction or preprocesses the new data. By analyzing the newly processed data through the server agent, the data user changes its role as the data provider. The data provider can also obtain useful statistical information from the Data Descriptor of the data it discloses and become a data user to perform new analysis using the sample data. In this way, raw data is processed and processed big data is utilized by the user, thereby forming a natural shared environment. The role of data provider and data user is not distinguished, and provides an ideal shared service that enables everyone to be a provider and a user. The client-server model solves the problem of sharing big data and provides a free sharing environment to securely big data disclosure and provides an ideal shared service to easily find big data.