• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.10
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• pp.909-916
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• 2016

The beacon receiver is an equipment which detects and measures the signal strength of transmitting satellite beacon signal. Beacon signals transmitted by satellites are low power continuous wave(CW) signals without any modulation intended for antenna steering to satellite direction and power control purposes on the earth. The beacon signal detection method using a very narrow band analog filter and RSSI(Received Signal Strength Intensity) has been typically used. However, it requires the implementation to track the frequency at the beacon receiver, thus a beacon frequency variation of the satellite due to temperature changes and long-term operation. Therefore, in this paper, the beacon signal detection receiver is designed by using a very narrow band digital filter array for a faster acquisition and SNR(Signal to Noise Ratio) method detection. For this purpose, by calculating the satellite link budget with the rain attenuation between satellite and ground station, and then extracting the received $C/N_o$ of the beacon signal, this work derives the bandwidth and the array number of the configured digital filter that gives the required C/N.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.12 no.4
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• pp.570-575
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• 2001

The minimum duration outage probability of a cellular system is defined the probability that the received signal level is hold under minimum required threshold duration. This definition is more realistic compared to the outage probability which is the received signal strength level is below predefined threshold level. Especially, in a DS-CDMA cellular system the received signal-to-interference ratio is a function of cell traffic, while the former researches are only considered the minimum duration outage probability independent of the cell traffic. We noticed that the minimum outage probability is rapidly increases as cell traffic increase.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1162-1179
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• 2017

In this paper, we propose indoor location tracking method using RSSI(Received Signal Strength Indicator) value received from BLE(Bluetooth Low Energy) beacon. Due to the influence of various external environmental factors, it is very difficult to improve the accuracy in indoor location tracking. In order to solve this problem, we propose a novel method of reducing the noise generated in the external environment by using a double Gaussian filter. In addition, the value of the RSSI signal generated in the BLE beacon is different for each device. In this study, we propose a method to allocate additional weights in order to compensate the intensity of signal generated in each device. This makes it possible to improve the accuracy of indoor location tracking using beacons. The experiment results show that the proposed method effectively decrease the RSSI deviation and increase location accuracy. In order to verify the usefulness of this study, we compared the Kalman filter algorithm which is widely used in signal processing. We further performed additional experiments for application area for indoor location service and find that the proposed scheme is useful for BLE-based indoor location service.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.85-90
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• 2017

Indoor location-based services have been developed based on the Internet of Things technologies which measure and analyze users who are moving in their daily lives. These various indoor positioning technologies require separate hardware and have several disadvantages, such as a communication protocol which becomes complicated. Based on the fact that a reduction in signal strength occurs according to the distance due to the physical characteristics of the transmitted signal, RSSI technology that uses the received signal strength of the wireless signal used in this paper measures the strength of the transmitted signal and the intensity of the attenuated received signal and then calculates the distance between a transmitter and a receiver, which requires no separate costs and makes to implement simple measurements. It was applied calculating the value for the average RSSI and the RSSI filtering feedback. Filtering is used to reduce the error of the RSSI values that are measured at long distance.It was confirmed that the RSSI values through the average filtering and the RSSI values measured by setting the coefficient value of the feedback filtering to 0.5 were ranged from -61 dBm to - 52.5 dBm, which shows irregular and high values decrease slightly as much as about -2 dBm to -6 dBm as compared to general measurements.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.2
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• pp.85-93
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• 2012

In this paper, we proposed Wireless LAN (WLAN) localization method that enhances database construction based on weighting factor and analyse the characteristic of the WLAN received signals. The weighting factor plays a key role as it determines the importance of Received Signal Strength Indication (RSSI) value from number of received signals (frequency). The fingerprint method is the most widely used method in WLAN-based positioning methods because it has high location accuracy compare to other indoor positioning methods. The fingerprint method has different location accuracies which depend on training phase and positioning phase. In training phase, intensity of RSSI is measured under the various. Conventional systems adapt average of RSSI samples in a database construction, which is not quite accurate due to variety of RSSI samples. In this paper, we analyse WLAN RSSI characteristic from anechoic chamber test, and analyze the causes of various distributions of RSSI and its influence on location accuracy in indoor environments. In addition, we proposed enhanced weighting factor algorithm for accurate database construction and compare location accuracy of proposed algorithm with conventional algorithm by computer simulations and tests.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.339-346
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• 2011

In the existing RF communication based WPAN environment, a lowering of battery span and interference problem among sensors occur because the value of output is set and transmitted steadily when the system on sensor is initialized. Therefore, this paper proposes a framework and a transmit method with low power which decreases the electricity consumption by properly controling transmit power of opponent by received signal strength indicator(RSSI) of each sensor. The system proposes a power-lowering method by controling transmit power properly by the transmit intensity of the connected sensor after being affected by the transmit intensity of surrounded sensor. The framework that is proposed in this paper includes data transmit module, transmit power manager module, transmit power searching module, signal transmit module, and signal receiving module.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1342-1345
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• 1993

In the cellular mobile communications as decreasing the cell radius to increse the reuse factor of frequencies, the handoff requests are increasing so that the efficient handoff decision making becomes a crucial problem. In this simulation study, we evaluate a set of handoff algorithms based on fuzzy-multicriteria decision making. These algorithms uses the parameters including the received signal strength intensity, the bit error rate and the distance between a mobile station and a base station. We compare the fuzzy algorithms in terms of call block ratio and handoff request ratio and call force ratio, and show the applicability of those algorithms in the cellular mobile communication systems.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.6
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• pp.379-392
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• 2016

This paper presents the design and simulation of a laser power beaming (LPB) system for an electric vehicle that establishes an optimal power transmission path based on the received signal strength. The LPB system is possible to transfer power from multiple transmitters to a single receiver according to the characteristics of the laser and the solar panel. When the laser beams of multiple transmitters aim at a solar panel at the same time, the received power is the sum of all energy at a solar panel. Our proposed LPB system consists of multiple transmitters and multiple receivers. The transmitter sends its power characteristics as optically coded pulses with a class 1 laser beam and powers as a high-intensity laser beam. By using the attenuated power level, the receiver can estimate the maximum receivable powers from the transmitters and select optimal transmitters. Throughout the simulation, we verified the possibility that different LPB receivers were achieved their required power by the optimal allocation of the transmitter among the various transmitters.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.7
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• pp.647-654
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• 2016

Indoor localization based on visible-light communication using the received signal strength intensity (RSSI) has been widely studied because of its high accuracy compared with other wireless localization methods. However, because the RSSI can vary according to the inclination and azimuth of the receiver, a large error can occur, even at the same position. In this paper, we propose a visible-light communication-based 3-D indoor positioning algorithm using the Gauss-Newton technique in order to reduce the errors caused by the change in the inclination of the receiver. The proposed system reduces the amount of computations by selecting the initial position of the receiver through the linear least-squares method (LSM), which is applied to the RSSIs, and improves the position accuracy by applying the Gauss-Newton technique to the 3-D nonlinear model that contains the RSSIs acquired by the changes in the azimuth and inclination of the receiver. In order to verify the validity of the proposed algorithm in an indoor space with dimensions of $6{\times}6{\times}3m$ where 16 LED lights are installed, we compare and analyze the errors of the conventional linear LSM-based trilateration technique and the proposed algorithm according to the changes in the inclination and azimuth of the receiver. The experimental results show that the location accuracy of the proposed algorithm is improved by 82.5% compared to the conventional LSM-based trilateration technique.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.9
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• pp.836-841
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• 2016

An indoor positioning system using Wi-Fi is essential to produce a radio map that combines the indoor space of two or more dimensions, the information of node positions, and etc. in processing for constructing the radio map, the measurement of the received signal strength indicator(RSSI) and the confirmation of node placement information counsume substantial time. Especially, when the installed wireless environment is changed or a new space is created, easy installation of the node and fast indoor radio mapping are needed to provide indoor location-based services. In this paper, to reduce the time consumption, we propose an algorithm to distinguish the straight and curve lines of a corridor section by RSSI visualization and Sobel filter-based edge detection that enable accurate node deployment and space analysis using cable-type Wi-Fi node installed at a 3 m interval. Because the cable type Wi-Fi is connected by a same power line, it has an advantage that the installation order of nodes at regular intervals could be confirmed accurately. To be able to analyze specific sections in space based on this advantage, the distribution of the signal was confirmed and analyzed by Sobel filter based edge detection and total RSSI distribution(TRD) computation through a visualization process based on the measured RSSI. As a result to compare the raw data with the performance of the proposed algorithm, the signal intensity of proposed algorithm is improved by 13.73 % in the curve section. Besides, the characteristics of the straight and the curve line were enhanced as the signal intensity of the straight line decreased by an average of 34.16 %.