• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.2
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• pp.27-37
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• 2022

In this paper, we presents a Multiple User Multiple Input Multiple Output (MU-MIMO) test-bed system for Time Division Duplex (TDD) Long Term Evolution-Advanced (LTE-A). Using two parameters, the condition number of the channel matrix and the path gain, the MU-MIMO system could switch pre-coder to maintain target Bit Error Rate (BER) level. This paper also introduces a calibration procedure for compensating error of Radio Frequency (RF) paths of the antennas and RF transceivers. From experimental measurements, dynamic pre-coding scheme could maintain target BER, set to 10^-3, with the pre-coder set configured with Zero Forcing (ZF), Tomlinson Harashima Pre-coding (THP), Lattice Reduction (LR). The simplest pre-coder ZF is adopted in stable channel, and when path gain become less than 0.25, LR is adopted. Lastly, when condition number of channel matrix become larger than 7, THP is adopted.

• Journal of Korea Multimedia Society
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• v.19 no.10
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• pp.1792-1807
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• 2016

Android application is vulnerable to reverse engineering attack. And by this, it is easy to extract significant module from source code and repackage it. To prevent this problem, dynamic class loading technique, which is able to exclude running code from distributed source code and is able to load running code dynamically during runtime can be used. Recently, this technique was adapted on variety of fields and applications like updating pre-loaded android application, preventing from repacking malicious application, etc. Despite the fact that this technique is used on variety of fields and applications, there is fundamental lack on the study of potential weakness or related secure coding. This paper would deal with potential weaknesses during the implementation of dynamic class loading technique with analysing related international/domestic standard of weaknesses and suggest a secure way for the implementation of dynamic class loading technique. Finally, we believe that this technique described here could increase the level of trust by decreasing the weakness related to dynamic class loading technique.

• ETRI Journal
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• v.38 no.5
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• pp.858-867
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• 2016

A high dynamic range (HDR) video service is an upcoming issue in the broadcasting industry. For compatibility with legacy devices receiving a non-constant luminance (NCL) signal, new tools supporting an HDR video service are required. The current pre-processing chain of HDR video can produce color noise owing to the chroma component down-sampling process for video encoding. Although a luma adjustment method has been proposed to solve this problem, some disadvantages still remain. In this paper, we present an adaptive color noise reduction method for an NCL signal of an HDR video service. The proposed method adjusts the luma component of an NCL signal adaptively according to the information of the luma component from a constant luminance signal and the level of color saturation. Experiment results show that the color noise problem is resolved by applying our proposed method. In addition, the speed of the pre-processing is increased more than two-fold compared to a previous method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.4
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• pp.646-652
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• 2015

In this paper, the system-level performance is evaluated for the feedback scheme on the pre-coding matrix index (PMI) and channel quality indication (CQI), which are required for user selection in the multi-user MIMO system. Our analysis demonstrates that the number of users, the number of selected users, and codebook size are the key factors that govern the performance of the best companion grouping (BCG)-based user scheduling. Accordingly, we have confirmed that the probability of forming the co-scheduled user group is determined by these factors, which implies that the number of PMI's and codebook size can be dynamically determined so as to maximize the average system throughput as the number of users varies in the cell.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.178-184
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• 2015

This paper proposes a hardware architecture for high performance Deblocking filter(DBF) in High Efficiency Video Coding for UHD(Ultra High Definition) videos. This proposed hardware architecture which has less processing time has a 4-stage pipelined architecture with two filters and parallel boundary strength module. Also, the proposed filter can be used in low-voltage design by using clock gating architecture in 4-stage pipeline. The segmented memory architecture solves the hazard issue that arises when single port SRAM is accessed. The proposed order of filtering shortens the delay time that arises when storing data into the single port SRAM at the pre-processing stage. The DBF hardware proposed in this paper was designed with Verilog HDL, and was implemented with 22k logic gates as a result of synthesis using TSMC 0.18um CMOS standard cell library. Furthermore, the dynamic frequency can process UHD 8k($7680{\times}4320$) samples@60fps using a frequency of 150MHz with an 8K resolution and maximum dynamic frequency is 285MHz. Result from analysis shows that the proposed DBF hardware architecture operation cycle for one process coding unit has improved by 32% over the previous one.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.180-191
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• 2016

When up-scaling algorithms for visible light images are applied to infrared (IR) images, they rarely work because IR images are usually blurred. In order to solve such a problem, this paper proposes an up-scaling algorithm for IR images. We employ adaptive dynamic range encoding (ADRC) as a simple classifier based on the observation that IR images have weak details. Also, since human visual systems are more sensitive to edges, our algorithm focuses on edges. Then, we add pre-processing in learning phase. As a result, we can improve visibility of IR images without increasing computational cost. Comparing with Anchored neighborhood regression (A+), the proposed algorithm provides better results. In terms of just noticeable blur, the proposed algorithm shows higher values by 0.0201 than the A+, respectively.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.11
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• pp.73-81
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• 2016

In general, infrared images have less sharpness and image details than visible images. So, the prior image upscaling methods are not effective in the infrared images. In order to solve this problem, this paper proposes an algorithm which initially up-scales an input infrared (IR) image by using adaptive dynamic range encoding (ADRC)-based super-resolution (SR) method, and then fuses the result with the corresponding visible images. The proposed algorithm consists of a up-scaling phase and a fusion phase. First, an input IR image is up-scaled by the proposed ADRC-based SR algorithm. In the dictionary learning stage of this up-scaling phase, so-called 'pre-emphasis' processing is applied to training-purpose high-resolution images, hence better sharpness is achieved. In the following fusion phase, high-frequency information is extracted from the visible image corresponding to the IR image, and it is adaptively weighted according to the complexity of the IR image. Finally, a up-scaled IR image is obtained by adding the processed high-frequency information to the up-scaled IR image. The experimental results show than the proposed algorithm provides better results than the state-of-the-art SR, i.e., anchored neighborhood regression (A+) algorithm. For example, in terms of just noticeable blur (JNB), the proposed algorithm shows higher value by 0.2184 than the A+. Also, the proposed algorithm outperforms the previous works even in terms of subjective visual quality.