• Journal of Satellite, Information and Communications
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• v.10 no.2
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• pp.24-29
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• 2015

Recently, with developments of various networks, devices and various services, energy efficiency has become one of the most crucial issues with respect to sustainability of mobile devices. For connecting to networks seamlessly to offer services, a scenario of RF energy harvesting which supplies energy to wireless devices with RF signals is assumed. To increase the efficiency of RF energy harvesting, this paper proposes a RF energy harvesting algorithm which is based upon a frequency selective fading map. Through the algorithm, a receiver of mobile device can get fading information at each frequency and select a frequency which has the best quality. At the end, the simulation result demonstrates its superiority by showing a 4.45dB improvement in comparison to a deep fading frequency point.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.3
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• pp.346-355
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• 2016

In this paper, we propose a method to analyze the clusters of RF threats emitting electrical signals based on collected signal variables in integrated electronic warfare environments. We first analyze the signal variables collected by an electronic warfare receiver, and construct a model based on variables showing the properties of threats. To visualize the distribution of RF threats and reversely identify them, we use k-means clustering algorithm and self-organizing map (SOM) algorithm, which are belonging to unsupervised learning techniques. Through the resulting model compiled by k-means clustering and SOM algorithms, the RF threats can be classified into one of the distribution of RF threats. In an experiment, we measure the accuracy of classification results using the algorithms, and verify the resulting model that could be used to visually recognize the distribution of RF threats.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.12
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• pp.1061-1068
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• 2013

In this paper, we propose a $M{\times}M$ beam-space multiple input multiple output (BS-MIMO) system using electronically steerable parasitic array radiator (ESPAR) antenna. Conventional MIMO method required multiple RF chains because it map the transmission signals onto multiple antennas. So, conventional MIMO system has high cost for design and high energy consumption at RF circuit. Also, It is difficult to use MIMO system in battery based mobile terminals with limited physical area. In order to solve these problems, BS-MIMO technique which map the data signal onto bases in beam space domain was proposed using ESPAR antenna with single RF chain. This paper, we design and analyze the performance of extended $M{\times}M$ BS-MIMO technique. Simulation results show that the proposed BS-MIMO system has similar BER performance compare to conventional MIMO scheme. Therefore, BS-MIMO system with single RF chain will has a low RF power consumption and low cost for RF hardware design as compared with conventional MIMO technique with multiple RF chains.

• Bulletin of the Korean Mathematical Society
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• v.42 no.1
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• pp.157-164
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• 2005

Let $RRat_k$ ($CP^n$) denote the space of basepoint-preserving conjugation-equivariant holomorphic maps of degree k from $S^2$ to $CP^n$. A map f ; $S^2 {\to}CP^n$ is said to be full if its image does not lie in any proper projective subspace of $CP^n$. Let $RF_k(CP^n)$ denote the subspace of $RRat_k(CP^n)$ consisting offull maps. In this paper we determine $H{\ast}(RF_k(CP^2); Z/p)$ for all primes p.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.4
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• pp.431-441
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• 2016

Since the use of UAV (Unmanned Aerial Vehicle) is convenient for the acquisition of data on broad or inaccessible regions, it is nowadays used to establish spatial information for various fields, such as the environment, ecosystem, forest, or for military purposes. In this study, the process of estimating FVC (Fractional Vegetation Cover), based on multi-spectral UAV, to overcome the limitations of conventional methods is suggested. Hence, we propose that the FVC map is generated by using multi-spectral imaging. First, two types of result classifications were obtained based on RF (Random Forest) using RGB images and NDVI (Normalized Difference Vegetation Index) with RGB images. Then, the result map was reclassified into vegetation and non-vegetation. Finally, an FVC map-based RF were generated by using pixel calculation and FVC map-based GI (Gutman and Ignatov) model were indirectly made by fixed parameters. The method of adding NDVI shows a relatively higher accuracy compared to that of adding only RGB, and in particular, the GI model shows a lower RMSE (Root Mean Square Error) with 0.182 than RF. In this regard, the availability of the GI model which uses only the values of NDVI is higher than that of RF whose accuracy varies according to the results of classification. Our results showed that the GI mode ensures the quality of the FVC if the NDVI maintained at a uniform level. This can be easily achieved by using a UAV, which can provide vegetation data to improve the estimation of FVC.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.1
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• pp.60-63
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• 2009

In this paper, Designed and implemented about module that generate division signal for uplink section and downlink section for controlling Tx/Rx antenna of 2.3-2.7GHz WiMAX TDD repeater. It is consisted of RF block and Baseband block, and because function of this module is that synchronize with WiMAX signal and create division signal for uplink section and downlink section, this module was designed only received path. And because of manufacturing of most RF block by one chip, this module could minimize area. And in baseband block, used the WiMAX Modem to detect Preamble and DL-MAP information of WiMAX signal. This design can process about 2.3-2.7GHz WiMAX.

• Journal of IKEEE
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• v.27 no.4
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• pp.650-656
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• 2023

This paper implements a channel model for mmWave bands using an NS-3-based 5G system-level simulator and analyzes the reliability and validity of the implemented model through RF performance verification. The channel model for RF performance verification in the mmWave bands consider parameters such as characteristics defined in 3GPP TR 38.901, beam-forming, antenna configuration, scenarios, among others. Furthermore, the simulation results verify compliance within the ranges permitted by the 3GPP standards and verify reliability in indoor environmental scenarios by exploiting the Radio Environment Map (REM). Therefore, the channel model implemented in this study is applicable to the actual design and establishment of 5G networks, presenting a method to evaluate and validate RF performance by adjusting various parameters.

• Korean Journal of Remote Sensing
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• v.34 no.4
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• pp.671-680
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• 2018

Compared to the imagery produced by traditional satellites, PlanetScope satellite imagery has made it possible to easily capture remotely-sensed imagery every day through dozens or even hundreds of satellites on a relatively small budget. This study aimed to detect changed areas and update a land cover map using a PlanetScope image. To generate a classification map, pixel-based Random Forest (RF) classification was performed by using additional features, such as the Normalized Difference Water Index (NDWI) and the Normalized Difference Vegetation Index (NDVI). The classification result was converted to vector data and compared with the existing land cover map to estimate the changed area. To estimate the accuracy and trends of the changed area, the quantitative quality of the supervised classification result using the PlanetScope image was evaluated first. In addition, the patterns of the changed area that corresponded to the classification result were analyzed using the PlanetScope satellite image. Experimental results found that the PlanetScope image can be used to effectively to detect changed areas on large-scale land cover maps, and supervised classification results can update the changed areas.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3789-3809
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• 2014

Radio environment maps (REMs) and geolocation database represent an important source of information for the operation of cognitive radio networks, replacing or complementing spectrum sensing information. This paper provides a survey of methods for constructing the radio frequency layer of radio environment map (RF-REM) using distributed measurements of the signal levels at a given frequency in space and time. The signal level measurements can be obtained from fixed or mobile devices capable of sensing radio environment and sending this information to the REM. The signal measurements are complemented with information already stored in different REM content layers. The combined information is applied for estimation of the RF-REM layer. The RF-REM construction methods are compared, and their advantages and disadvantages with respect to the spatial distribution of signal measurements and computational complexity is given. This survey also indicates possible directions of further research in indirect RF-REM construction methods. It emphasizes that accurate RF-REM construction methods should in the best case support operation with random and clustered signal measurements, their operation should not be affected by measurements outliers, and it must estimate signal levels comparably on all RF-REM locations with moderate computational effort.

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.50-55
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• 2023

Due to the unavailability of global positioning system (GPS) indoors, various indoor pedestrian positioning methods have been designed to estimate the position of the user using received signal strength (RSS) measurements from radio beacons, such as wireless fidelity (WiFi) access points and Bluetooth low energy (BLE) beacons. In indoor environments, radio-frequency (RF) signals are unpredictable and change over space and time because of multipath associated with reflection and refraction, shadow fading caused by obstacles, and interference among different devices using the same frequencies. Therefore, the outliers in the positional information obtained from the indoor positioning method based on RSS measurements occur often. For this reason, the performance of the positioning method can be degraded by the characteristics of the RF signal. To resolve this issue, a map-matching (MM) algorithm based on maximum probability (MP) estimation is applied to the indoor positioning method in this study. The MM algorithm locates the aberrant position of the user estimated by the positioning method within the limits of the adjacent pedestrian passages. Empirical experiments show that the positioning method can achieve higher positioning accuracy by leveraging the MM algorithm.