• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5C
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• pp.527-539
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• 2009

In this paper, we propose an asynchonous ICI (Inter-Cell Interference) mitigation techniques for 3GPP LTE MIMO-OFDMA down-link receiver. An increasing in symbol timing misalignments may occur relative to sychronous network as the result of BS (Base Station) timing differences. Such symbol synchronization errors that exceed the guard interval or the cyclic prefix duration may result in MAI (Multiple Access Interference) for other carriers. In particular, at the cell boundary, this MAI becomes a critical factor, leading to degraded channel throughput and severe asynchronous ICI. Hence, many researchers have investigated the interference mitigation method in the presence of asynchronous ICI and it appears that the knowledge of the SCM (Spatial Covariance Matrix) of the asynchronous ICI plus background noise is an important issue. Generally, it is assumed that the SCM estimated by using training symbols. However, it is difficult to measure the interference statistics for a long time and training symbol is also not appropriate for MIMO-OFDMA system such as LTE. Therefore, a noise reduction method is required to improve the estimation accuracy. Although the conventional time-domain low-pass type weighting method can be effective for noise reduction, it causes significant estimation error due to the spectral leakage in practical OFDM system. Therefore, we propose a time-domain sinc type weighing method which can not only reduce the noise effectively minimizing estimation error caused by the spectral leakage but also implement frequency-domain moving average filter easily. By using computer simulation, we show that the proposed method can provide up to 3dB SIR gain compared with the conventional method.

• Journal of Advanced Navigation Technology
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• v.12 no.4
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• pp.332-340
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• 2008

In this paper, comparisons of the superimposition schemes for orthogonal frequency division multiplexing (OFDM) system are made. The time domain superimposition of data (TDSD) has a tradeoff between the degree of freedom for data transmission and inter-carrier interference (ICI). While SPPT and APSB experiences the increases of interference as the transmit data rate increases, TDSD can effectively improve spectral efficiency by exploiting preprocessing structures which prevents interference between the signals in the different domain. TDSD which we proposed is compared with the conventional superimposition schemes or OFDM, such as SPPT (the superimposed periodic pilot in the time domain) and APSB (the added pilot semi-blind channel estimation) by simulation. As the result, comparing the conventional OFDM, TDSD can increase the spectral efficiency up to about 20% with the superimposition factor M=16 while SPPT has the similar efficiency. APSB has the worst efficiency.

• The Journal of the Acoustical Society of Korea
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• v.24 no.7
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• pp.402-409
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• 2005

In this paper. we propose a coding method using a matching pursuit algorithm in a strongly periodic highband signal. Also. we propose an efficient quantizer for the estimated parameters : spectral magnitude and phase. Based on the error concealment principle and sinusoidal model. the MP algorithm requires the high-precision pitch period estimation. To estimate more accurate pitch period. the refined pitch obtained from lowband speech is used. which increases the efficiency of bit allocation. The spectral magnitude parameters are quantized by the method which is combined with MDCT (Modified Discrete Cosine Transform) and multi-stage structure. The spectral phase quantizer uses the $2{\pi}$ modular characteristic of phases and the weighted function by spectral magnitudes. To evaluate the efficiency of the proposed method. we applied it to analysis-by-synthesis system. Furthermore we suggest the possibillity of scalable wideband speech codecs based on band-split structure.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.28 no.4
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• pp.383-391
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• 2009

In speech signal processing, speech signal corrupted by noise should be enhanced to improve quality. Usually noise estimation methods need flexibility for variable environment. Noise profile is renewed on silence region to avoid effects of speech properties. So we have to preprocess finding voice region before noise estimation. However, if received signal does not have silence region, we cannot apply that method. In this paper, we proposed SNR estimation method for continuous speech signal. The waveform which is stationary region of voiced speech is very correlated by pitch period. So we can estimate the SNR by correlation of near waveform after dividing a frame for each pitch. For unvoiced speech signal, vocal track characteristic is reflected by noise, so we can estimate SNR by using spectral distance between spectrum of received signal and estimated vocal track. Lastly, energy of speech signal is mostly distributed on voiced region, so we can estimate SNR by the ratio of voiced region energy to unvoiced.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.18-25
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• 2020

In the fifth generation (5G) and beyond 5G (B5G) mobile communication, non-orthogonal multiple access (NOMA) has attracted great attention due to higher spectral efficiency and massive connectivity. We investigate the impacts of the channel estimation errors on the bit-error rate (BER) of NOMA, especially with the single-user decoding (SUD) receiver, which does not perform successive interference cancellation (SIC), in contrast to the conventional SIC NOMA scheme. First, an analytical expression of the BER for SUD NOMA with channel estimation errors is derived. Then, it is demonstrated that the BER performance degrades severely up to the power allocation less than about 20%. Additionally, we show that for the fixed power allocation of 10% in such power allocation range, the signal-to-noise (SNR) loss owing to channel estimation errors is about 5 dB. As a consequence, the channel estimation error should be considered for the design of the SUD NOMA scheme.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.25-28
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• 2002

The aim of the present study was the evaluation of methods for estimating the vegetation information in the field on the basis of spectral reflectance measured farm field, in particular the estimation of Leaf Area Index(LAI). Variability in tissue optical properties was wavelength-dependent. For rice and bean, the lowest variation was in the visible spectral region and the highest in the near-infrared. The structural attributes of ecosystems determine the relative contribution of tissue and canopy factors that drive variation in a reflectance signal.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.12
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• pp.169-171
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• 1994

This paper is to find out more reliable analyzing method of heart rate variability. Heart rate variability analysis is to evaluate cardiovascular stability and also have used as an indicator of autonomic nervous system activity. In this study, time domain analysis, spectral analysis and state space analysis method are applied to analyze heart rate variability. Because of nonlinear characteristics of heart rate, we need not only spectral analysis, but also state space analysis. Fractal dimension of spectral estimation is useful indicator of autonomic nervous activity.

• Structural Engineering and Mechanics
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• v.68 no.1
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• pp.39-51
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• 2018

In this study, a frequency domain model updating method is presented using power spectral density (PSD) data. It uses the sensitivity of PSD function with respect to the unknown structural parameters through a decomposed form of transfer function. The stiffness parameters are captured with high accuracy through solving the sensitivity equations utilizing the least square approach. Using numerically noise polluted data, the model updating results of a truss model prove robustness of the method against measurement and mass modelling errors. Results prove the capabilities of the method for parameter estimation using highly noise polluted data of low ranges of excitation frequency.

• Journal of Astronomy and Space Sciences
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• v.33 no.2
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• pp.101-104
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• 2016

More than 100 γ−ray pulsars have been discovered by the Fermi Gamma-ray Space Telescope. With a significantly enlarged sample size, it is possible to compare the properties of different classes. Radio-quiet (RQ) γ−ray pulsars form a distinct population, and various studies have shown that the properties of the RQ population can be intrinsically different from those of radio-loud (RL) pulsars. Utilizing these differences, it is possible to further classify the pulsar-like unidentified γ−ray sources into sub-groups. In this study, we suggest the possibility of distinguishing RQ/RL pulsars by their spectral shape. We compute the probabilities of a pulsar to be RQ or RL for a given spectral curvature. This can provide a key to the estimation of the intrinsic fraction of radio-quietness in the γ−ray pulsar population, which can place a tight constraint on the emission geometry.