• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.2B
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• pp.159-167
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• 2011

LTE-Advanced system requires uplink multi-antenna transmission in order to achieve the peak spectral efficiency of 15bps/Hz. In this paper, the uplink MIMO system model for the LTE-Advanced is proposed and an efficient link adaptation shceme using precoding is considered providing error rate reduction and system capacity enhancement. In particular, the proposed scheme determines a transmission rank by selecting the optimal wideband precoding matrix, which is based on the derived signal-to-interference and noise ratio (SINR) for the minimum mean squared error (MMSE) receivers of $2{\times}4$ multiple input multiple output (MIMO). The proposed scheme is verified by simulation with a practical MIMO channel model. The simulation results of average block-error-rate(BLER) reflect that the gain due to the proposed rank adapted transmission over full-rank transmission is evident particularly in the case of lower modulation and coding scheme (MCS) and high mobility, which means the severe channel fading environment.

• Journal of Broadcast Engineering
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• v.17 no.3
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• pp.471-479
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• 2012

Intra prediction is one of the significant techniques in H.264/AVC reference software; however, it has heavy computational complexity. In order to solve this problem, many fast algorithms have been proposed. In this paper, we propose a fast intra mode decision algorithm which predicts the edge direction of the current block using sub-sampled pixels to reduce high computational complexity of the H.264/AVC encoder. The proposed algorithm shows that it not only improves the coding performance but also reduces the computational complexity of the H.264/AVC encoder compared to previous algorithms. The experimental results show that the proposed algorithm achieves the encoding time reduction of 75.93% on an average with slight peak signal-to-noise ratio (PSNR) drop and bit-rate increment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.11
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• pp.918-926
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• 2012

In 3D video transmission, a depth map being used for depth image based rendering (DIBR) is generally compressed by reducing resolution for coding efficiency. Errors in resolution reduction are recovered by an appropriate up-sampling method after decoding. However, most previous works only focus on up-sampling techniques to reduce errors. In this paper, we propose a novel down-sampling technique of depth map that applies different down-sampling rates on moving objects and background in order to enhance human perceptual quality. Experimental results demonstrate that the proposed scheme provides both higher visual quality and peak signal-to-noise ratio (PSNR). Also, our method is compatible with other up-sampling techniques.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.8
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• pp.1165-1171
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• 2010

The OFDM system has better characteristics in transmission rate, power efficiency, bandwidth efficiency, impulse-noise immunity, and narrow band interference immunity etc. in comparison with other conventional systems. However, high PAPR of an OFDM signals causes some serious non-linear processing of RF amplifier. And performance of the communication system gets worse. Therefore, various methods reducing PAPR of an OFDM skills such as the clipping method, block coding method, and phase rotation method etc. have been researched. In this paper, we propose a high-speed adaptive PTS method which eliminates high PAPR. And we compare the proposed method with other conventional methods. The proposed method has decreased quantity of calculation compare with an adaptive PTS method. Of course, The more its calculation amount is decreased, the more its BER characteristic is not better than an adaptive PTS method. However, keeping up satisfactory BER performance, we highly improved calculation amount of a PTS method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.5
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• pp.1-10
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• 2007

Most of natural images have a special property, what is called self-similarity, which is the basis of fractal image coding. Even though an image has local stationarity in several homogeneous regions, it is generally non-stationarysignal, especially in edge region. This is the main reason that poor results are induced in linear techniques. In order to overcome the difficulty we propose a non-linear technique using self-similarity in the image. In our work, an image is classified into stationary and non-stationary region with respect to sample variance. In case of stationary region, do-noising is performed as simply averaging of its neighborhoods. However, if the region is non-stationary region, stationalization is conducted as make a set of center pixels by similarity matching with respect to bMSE(block Mean Square Error). And then do-nosing is performed by Gaussian weighted averaging of center pixels of similar blocks, because the set of center pixels of similar blocks can be regarded as nearly stationary. The true image value is estimated by weighted average of the elements of the set. The experimental results show that our method has better performance and smaller variance than other methods as estimator.