• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.16 no.10 s.101
• /
• pp.1010-1019
• /
• 2005

In this paper, we used neural network technique to model memory effects of RF power amplifier which is fed by two-tone input signals. The memory effects in power amplifier were identified by observing the unsymmetrical distribution of IMD(Inter-Modulation Distortion) measurements with the change of tone spacings and power levels. Different asymmetries of IMD were also found at different center frequencies. We applied TDNN technique to model LDMOS power amplifier based on two tone IMD data, and the accuracy was very high compared to other modeling methods such as the(memoryless) adaptive modeling method.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.21 no.8
• /
• pp.462-467
• /
• 2009

Researches and developments on BEMS are performed world-widely through sustainable management in various conditions. However, there are many obstacles to adapt the system in existing buildings because it needs highly expensive equipments, which are designed for newly built buildings, to install. Therefore, there are numerous limits exist when applying the BEMS in established buildings. The purpose of this study estimates the optimization of RF output power in WSN(Wireless Sensor Networks), which is the essential technology to develop PEMS. The results of this study is as follows ; 1) Applying WSN technique in buildings was possible. 2) As RF output power increases, the number of relay node reduced, therefore, the WSN showed more stability. 3) When estimating optimal RF output power in school, it should be considered between the number of relay node and RF output power. 4) Considering battery consumption and possibility of reception, the best suited RF output power is -20dbm in apartment house.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.17 no.4
• /
• pp.159-167
• /
• 2018

In this paper, we propose an algorithm to optimize energy efficiency in a multi-user decoupled RF energy harvesting network and experiment on the trend of energy efficiency change assuming users' various geographical distribution scenarios. In the RF energy harvesting network where both wireless data transmission and RF energy harvesting are simultaneously performed, the energy efficiency is a key indicator of network performance, and it is necessary to investigate how various factors can affect the energy efficiency. In order to increase energy efficiency effectively, we can confirm that users' distributions are important factors in the RF energy harvesting network from the simulation results.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.44 no.3
• /
• pp.37-42
• /
• 2007

This paper reconsiders established power conservation models for ubiquitous sensor networks that use relay nodes instead of direct communication and proposes novel network power consumption model with consideration of the channel level and radio chip level simultaneously. We estimate the effect of minimum hop-count policy in terms of network power consumption through simulation of various situations for low power RF module CC2420. It is observed that maximum RF power and minimum hop-count results in lower energy consumption relatively. Also, in total network energy consumption, which is included re-transmission, minimum hop count policy presents decrease by 33.1% of energy consumption in compare with the conventional model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.10a
• /
• pp.719-722
• /
• 2016

These days there have been trying to fuse the various of IoT (Internet of Things) technology over the industrial field. However the complicated IoT System structure comprised of sensor devices, gateway, network server, and application server causes the difficulties to the system implementation and the increment of installation cost, thereby preventing IoT system deployment in the industry fit for small size network environment. In this paper, authors propose a novel IoT system architecture that is useful in the industry field to be implemented by the small size network with low cost. Also, we implement the infrastructure to RF433 wireless sensor network, the gateway on ARDUINO YUN, and the application server using AMP (Apache, PHP, MySQL) package and then present a power efficient management scheme for sensor devices.

• Journal of the Korean Vacuum Society
• /
• v.8 no.1
• /
• pp.75-82
• /
• 1999

Ion energy is one of the crucial property in thin film deposition by internal ICP assisted I-PVD. As ion energy is determined by the difference between the plasma potential and the substrate bias potential, ICP excitation frequency was tested with medium frequency of 4 MHz and two types of tuning circuits, alternate and floating LC network with a biasing resistor, were tested. The results showed that plasma potential was less than 5 V in a range of Ar pressures, 5mTorr to 30 mTorr, at 4 MHz RF 600 W and 60 V of maximum RF antenna voltage was maintained either at RF input or output terminal. By proper control of RLC circuit installed after after RF antenna, 50V of RF induced voltage on RF antenna was obtained at 500W input power. The total impedance of RF antenna and plasma was around 10$\Omega$, and minimum RF voltage was obtained with a condition of lowest reactance at most 0.05$\Omega$.

• Proceedings of the KIEE Conference
• /
• 2004.07d
• /
• pp.2173-2175
• /
• 2004

This paper addresses a telemetering device which uses RF transceivers and a mobile-phone. Locally collected data arc encoded with a BCH error correcting code and transferred to a receiver through a RF module. The receiver-side RF module decodes the transferred data and then repetes them to a mobile-phone. Lastly, the mobile-phone hands over the data through a wireless phone network to a host computer in the internet.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.53 no.2
• /
• pp.94-99
• /
• 2004

In this paper, We design a RF control system capable of handling multiple POS thermal printers. The system has three parts including embedded master controller, RF controller and high-speed thermal printer. Specially the designed linux embedded controller has simple structure and high performance to connect the TCP/IP network. The effectiveness of the developed RF control system is shown by proposed food ordering system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.15 no.1
• /
• pp.8-13
• /
• 2022

This paper investigates the method to implement a RF (Radio Frequency) energy harvesting sensor node and to build a sensor network using a CATV network and a leaky coaxial cable. The power supply of a sensor node is designed with the WPTS (Wireless Power Transfer System) receiver operating at 915MHz. A sensor network has limited coverage by the loss of RF signal at a wireless transmission link. The paper proposes to build a sensor network that the BLE signal of a sensor and the signal of a WPTS power transmitter are transmitted through a coaxial cable of a CATV network by utilizing WOC (WiFi over Coax) technology and radiates at a leaky coaxial cable. The length of a leaky coaxial cable and the total loss of a wire link are allowed to the point that the RSSI of a sensor node is more than the minimum value (-78dBm) and lead to extend wireless coverage.

• The Journal of Korean Institute of Next Generation Computing
• /
• v.14 no.6
• /
• pp.57-65
• /
• 2018

Conventional RF signal-based indoor localization techniques such as BLE or Wi-Fi based fingerprinting method show considerable localization errors even in small-scale indoor environments due to unstable received signal strength(RSS) of RF signals. Therefore, it is difficult to apply the existing RF-based fingerprinting techniques to large-scale indoor environments such as airports and department stores. In this paper, instead of RF signal we use the geomagnetic sensor signal for indoor localization, whose signal strength is more stable than RF RSS. Although similar geomagnetic field values exist in indoor space, an object movement would experience a unique sequence of the geomagnetic field signals as the movement continues. We use a deep neural network model called the recurrent neural network (RNN), which is effective in recognizing time-varying sequences of sensor data, to track the user's location and movement path. To evaluate the performance of the proposed geomagnetic field based indoor positioning system (IPS), we constructed a magnetic field map for a campus testbed of about $94m{\times}26$ dimension and trained RNN using various potential movement paths and their location data extracted from the magnetic field map. By adjusting various hyperparameters, we could achieve an average localization error of 1.20 meters in the testbed.