• ETRI Journal
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• v.45 no.4
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• pp.570-580
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• 2023

Sensor nodes are the most significant part of a wireless sensor network that offers a powerful combination of sensing, processing, and communication. One major challenge while designing a sensor node is power consumption, as sensor nodes are generally battery-operated. In this study, we proposed the design of a low-power, long range-based wireless sensor node with flexibility, a compact size, and energy efficiency. Furthermore, we improved power performance by adopting an efficient hardware design and proper component selection. The Nano Power Timer Integrated Circuit is used for power management, as it consumes nanoamps of current, resulting in improved battery life. The proposed design achieves an off-time current of 38.17309 nA, which is tiny compared with the design discussed in the existing literature. Battery life is estimated for spreading factors (SFs), ranging from SF7 to SF12. The achieved battery life is 2.54 years for SF12 and 3.94 years for SF7. We present the analysis of current consumption and battery life. Sensor data, received signal strength indicator, and signal-to-noise ratio are visualized using the ThingSpeak network.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.12
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• pp.1365-1372
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• 2014

In recent, the LTE(Long-Term Evolution) mobile communication system has been commercialized and a variety of service is being provided. Comparing to the old wireless access systems such as 3G mobile communications, in particular, the LTE system supports a service requiring a high transmission rate by providing broadband wireless access. In order to understand the possibility of successful support of a multimedia service such as IPTV(Internet Protocol Television) through the LTE system, it is necessary to understand the mechanism that decides the transmission rate supported by the LTE system. This paper, therefore, discusses on the relationship between a number of metrics such as CQI and BLER that affects the transmission rate with the measurement results from the field tests.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.7
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• pp.852-860
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• 2019

In this paper, we proposed a new trilateration technique based on exponential moving average (EMA) filter with adaptive signal model which enhances accuracy of positioning system even if the RSSI changes randomly due to movement of obstacles or blind node in indoor environment. In the proposed scheme, three fixed transmitters sent out the signal to blind node. The transmitter decides the location of the blind node based on RSSI and it estimates the cause of RSSI fluctuation which is interference of obstacle or movement of blind node. When the path between blind node and transmitter has become NLOS path because of obstacles, the transmitter ignores the measured RSSI in NLOS path and replace estimated RSSI in LOS environment. In the other case, the transmitter updated the new RSSI to represent of movement of blind node. The proposed scheme has been verified on a ZigBee testbed and we proved the improved positioning accuracy compared to the existing indoor position system.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.109-116
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• 2014

In recent, ISM (Industrial Scientific Medical) band that is 2.4GHz band authorized free of charge is being widely used for smart phone, notebook computer, printer and portable multimedia devices. Accordingly, studies have been continuously conducted on the possibility of coexistence among nodes using ISM band. In particular, the interference of IEEE 802.11b based Wi-Fi device using overlapping channel during communication among IEEE 802.15.4 based wireless sensor nodes suitable for low-power, low-speed communication using ISM band causes serious network performance deterioration of wireless sensor networks. This paper examined a method of identifying channel status to avoid interference among wireless communication devices using IEEE 802.11b (Wi-Fi) and other ISM bands during communication among IEEE 802.15.4 based wireless sensor network nodes in ISM band. To identify channels occupied by Wi-Fi traffic, various studies are being conducted that use the RSSI (Received Signal Strength Indicator) value of interference signal obtained through ED (Energy Detection) feature that is one of IEEE 802.15.4 transmitter characteristics. This paper examines an algorithm that identifies the possibility of using more accurate channel by mixing utilization of interference signal and RSSI mean value of interference signal by wireless sensor network nodes. In addition, it verifies such algorithm by using OPNET Network verification simulator.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.564-573
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• 2015

GPS is the representative positioning technology for providing the location information. This technique has the disadvantage that does not operate in the shadow areas, such as urban or dense forest and the interior. This paper proposes a hybrid indoor positioning algorithm, which estimates a more accurate location of the terminal using strength of the Wi-Fi signal from the indoor AP. To determine the location of the user, we establish the most appropriate path loss model for the measurement environment. by using the RSSI value measured in a variety of environment such as building structure, person, distance, etc. The path loss exponent obtained by the path loss model is changed according to the environment. REKF, PF estimate the position of the terminal by using measured value from the AP with path loss exponent. For more accurate position estimation, we select positioning system by the value of threshold measured by experiments rather than a single positioning system. Experimental results using the proposed hybrid algorithm show that the performance is improved by about 17% than the conventional single positioning method.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.4
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• pp.477-482
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• 2015

In this paper, an android platform with Unity engine was proposed for the effective 3D presentation of IoT sensor's position to IoT(Internet of Things) users. This android platform based home-gateway was designed with the cooperation of 3D unity engine for 3D texture according to MovieTexture simultaneously. As a result, the 3D presentation technology of IoT sensors was described with Unity based 3D modeling. In this proposed smart gateway, the 3D position was presented with the received RSSI(Received Signal Strength Indicator) and angle of IoT sensors. This 3D Unity launcher can be used for the 3D position, monitoring, and the life managing of IoT sensors with the beacon and 3 dimensional cube-style after the 3D conversion of 2D.

• 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.

• Journal of IKEEE
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• v.26 no.1
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• pp.62-66
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• 2022

Recently, there have been many research efforts based on data-based deep learning technologies to deal with the interference problem between heterogeneous wireless communication devices in unlicensed frequency bands. However, existing approaches are commonly based on the use of complex neural network models, which require high computational power, limiting their efficiency in resource-constrained network interfaces and Internet of Things (IoT) devices. In this study, we address the problem of classifying heterogeneous wireless technologies including Wi-Fi and ZigBee in unlicensed spectrum bands. We focus on a data-driven approach that employs a supervised-learning method that uses received signal strength indicator (RSSI) data to train Deep Convolutional Neural Networks (CNNs). We propose a simple measurement methodology for collecting RSSI training data which preserves temporal and spectral properties of the target signal. Real experimental results using an open-source 2.4 GHz wireless development platform Ubertooth show that the proposed sampling method maintains the same accuracy with only a 10% level of sampling data for the same neural network architecture.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.1
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• pp.119-133
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• 2009

The purpose of this research is to accurately estimate the location of a device using the received signal strength indicator (RSSI) of IEEE 802.11 WLAN for location tracking in indoor environments. For the location estimation method, we adopted the calibration model. By applying the Adaptive Zone Based K-NNSS (AZ-NNSS) algorithm, which considers the velocity of devices, this paper presents a 9% improvement of accuracy compared to the existing K-NNSS-based research, with 37% of the K-NNSS computation load. The accuracy is further enhanced by using a Kalman filter; the improvement was about 24%. This research also shows the level of accuracy that can be achieved by replacing a subset of the calibration data with values computed by a numerical equation, and suggests a reasonable number of calibration points. In addition, we use both the mean error distance (MED) and hit ratio to evaluate the accuracy of location estimation, while avoiding a biased comparison.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.7
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• pp.774-781
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• 2014

This paper presents a fingerprint database construction method for WLAN RSSI (Received Signal Strength Indicator)-based indoor positioning. When RSSI is used for indoor positioning, the fingerprint method can achieve more accurate positioning than trilateration and centroid methods. However, a FD (Fingerprint Database) must be constructed before positioning. This step is a very laborious process. To reduce the drawbacks of the fingerprint method, a radio propagation model-based FD construction method is presented. In this method, an FD can be constructed by a simulator. Experimental results show that the constructed FD-based positioning has a 3.17m (CEP) error. In this paper, a spatial correlation method is presented to estimate the NLOS(Non-Line of Sight) error included in the FD constructed by a simulator. As a result, the NLOS error of the FD is reduced and the performance of the error compensated FD-based positioning is improved. The experimental results show that the enhanced FD-based positioning has a 2.58m (CEP) error that is a reasonable performance for indoor LBS (Location Based Service).