• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.83-88
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• 2006

Many applications in the area of location-based services and personal navigation require nowadays the location determination of a user not only in outdoor environment but also indoor. To locate a person or object in a building, systems that use either infrared, ultrasonic or radio signals, and visible light for optical tracking have been developed. The use of WiFi for location determination has the advantage that no transmitters or receivers have to be installed in the building like in the case of infrared and ultrasonic based location systems. WiFi positioning technology adopts IEEE802.11x standard, by observing the radio signals from access points installed inside a building. These access points can be found nowadays in our daily environment, e.g. in many office buildings, public spaces and in urban areas. The principle of operation of location determination using WiFi signals is based on the measurement of the signal strengths to the surrounding available access points at a mobile terminal (e.g. PDA, notebook PC). An estimate of the location of the terminal is then obtained on the basis of these measurements and a signal propagation model inside the building. The signal propagation model can be obtained using simulations or with prior calibration measurements at known locations in an offline phase. The most common location determination approach is based on signal propagation patterns, namely WiFi fingerprinting. In this paper the underlying technology is briefly reviewed followed by an investigation of two WiFi positioning systems. Testing of the system is performed in two localization test beds, one at the Vienna University of Technology and the second at the Hong Kong Polytechnic University. First test showed that the trajectory of a moving user could be obtained with a standard deviation of about ${\pm}$ 3 m.

• Journal of Satellite, Information and Communications
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• v.9 no.2
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• pp.101-106
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• 2014

As ESL(Electronic Shelf Label) system is increased at the market in the world, the interference between ESL system and Wi-Fi(Wireless Fidelity) Cellular Phone at 2.4GHz becomes issue. The interference scenario and propagation of the Extended HATA Model were established to analyze the interference from Wi-Fi Cellular Phone into ESL system. Through simulation results based on SEAMCAT(Spectrum Engineering Advanced Monte Carlo Analysis Tool), separation distance was obtained to protect ESL system from Wi-Fi Cellular Phone interference.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.684-690
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• 2015

This paper presents a modified residual-based EKF (Extended Kalman Filter) for performance improvement of indoor positioning using WiFi RSSI (Received Signal Strength Indicator) measurement. Radio signal strength in indoor environments may have irregular attenuation characteristics due to obstacles such as walls, furniture, etc. Therefore, the performance of the RSSI-based positioning with the conventional trilateration method or Kalman filter is insufficient to provide location-based accurate information services. In order to enhance the performance of indoor positioning, in this paper, error analysis of the distance calculated by using the WiFi RSSI measurement is performed based on the radio propagation model. Then, an IARM (Irregularly Attenuated RSSI Measurement) error is defined. Also, it shows that the IARM error is included in the residual of the positioning filter. The IARM error is always positive. So, it is presented that the IARM error can be estimated by taking the absolute value of the residual. Consequently, accurate positioning can be achieved based on the IEM (IARM Error Mitigated) EKF with the residual modified by using the estimated IARM error. The performance of the presented IEM EKF is verified experimentally.

• Journal of Satellite, Information and Communications
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• v.11 no.4
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• pp.33-38
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• 2016

As a communications system and using the wireless devices is increased at the world, the interference among devices at 2.4GHz band become issue. New complex content technology as education, concert, broadcast, thema-park are developed between Virtual Reality technology and tradition. That is expect an annual growth rate of more than 14%. Almost Virtual Reality devices use motion sense or a wireless joystick. Therefore it is necessarily to analyze the coexistence between Virtual Reality devices and Wi-Fi in the ISM band. The interference scenario and propagation of the Extended Hata Model was established to analyze the interference from WLAN into Virtual Reality devices. Through simulation results based on Monte-Carlo principle, separation frequency was obtained to protect WLAN interference from Virtual Reality devices.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.25-30
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• 2024

Smart City, a key application area of the AIoT (Artificial Intelligence of Things), provides various services in safety, security, and healthcare sectors through location tracking and location-based services. an IPS (Indoor Positioning System) is required to implement location-based services, and wireless communication technologies such as WiFi, UWB (Ultra-wideband), and BLE (Bluetooth Low Energy) are being applied. BLE, which enables data transmission and reception with low power consumption, can be applied to various IoT devices such as sensors and beacons at a low cost, making it one of the most suitable wireless communication technologies for indoor positioning. BLE utilizes the RSSI (Received Signal Strength Indicator) to estimate the distance, but due to the influence of multipath fading, which causes variations in signal strength, it results in an error of several meters. In this paper, we conducted research on a path loss model that can be applied to BLE IPS for proximity services, and confirmed that optimizing the free space propagation loss coefficient can reduce the distance error between the Tx and Rx devices.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.12
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• pp.2221-2231
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• 2017

In this paper, we surveyed previous cases, network protocols (such as Wi-Fi, Zigbee, Z-wave, and WirelessHart) and propagation characteristics on the application of maintaining equipments for instrumentation and control (I&C) using wireless communication techniques inside the nuclear power plant (NPP). In addition, we compared and analyzed the difference of detailed regulations with respect to the electromagnetic interference (EMI) and radio frequency interference (RFI) in the Regulatory Guide 1.180 rev. 1 (RG. 1.180) for adopting the wireless communication techniques inside the NPP, and other regulations, such as MIL-STD 461E and IEC 61000-4, that are recognized in the KINS/RG-N03.09 (Rev. 2). Furthermore, we investigated evaluating factors about electromagnetic properties by considering indoor environments, wave scattering, shielding effectiveness, and the indoor wave attenuation model that were not included in the current electromagnetic compatibility regulation.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.13-20
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• 2022

IEEE 802.11ay Wi-Fi is the next generation wireless technology and operates in mmWave band. It supports the MU-MIMO (Multiple User Multiple Input Multiple Output) transmission in which an AP (Access Point) can transmit multiple data streams simultaneously to multiple STAs (Stations). To this end, the AP should perform MU-MIMO beamforming training with the STAs. For efficient MU-MIMO beamforming training, it is important for the AP to estimate signal strength measured at each STA at which multiple beams are used simultaneously. Therefore, in the paper, we propose a deep learning-based link quality estimation scheme. Our proposed scheme estimates the signal strength with high accuracy by utilizing a deep learning model pre-trained for a certain indoor or outdoor propagation scenario. Specifically, to estimate the signal strength of the multiple concurrent beams, our scheme uses the signal strengths of the respective single beams, which can be obtained without additional signaling overhead, as the input of the deep learning model. For performance evaluation, we utilized a Q-D (Quasi-Deterministic) Channel Realization open source software and extensive channel measurement campaigns were conducted with NIST (National Institute of Standards and Technology) to implement the millimeter wave (mmWave) channel. Our simulation results demonstrate that our proposed scheme outperforms comparison schemes in terms of the accuracy of the signal strength estimation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.740-748
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• 2016

IT and communication technologies has contributed significantly to the convenience of passengers and the financial management of stations in accordance with the task automation in the field of the urban railway system. The foundation of the above development is based on the large amounts of data from various sensors installed in railways, trains, and stations. In particular, the sensor network that is installed in the station and train has played an important role in the railway information system. The performance of AP is affected by the number of APs and their locations installed in the station. In the installation of APs in stations, the intensity of the radio wave of the AP on its underlying position is considered to determine the number and position of APs. This paper proposes a method to estimate the number of APs and their position based on the structure of the underlying station and implemented a simulator to simulate the performance of the proposed method. The implemented simulator was applied to the decision of AP installation at Busan Seomyeon station to evaluate its performance.