• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2004.05b
• /
• pp.489-493
• /
• 2004

본 논문에서는 다중경로 페이딩 환경에서의 하이브리드 (Hybrid) SC/MRC-L$_{c}$/L 다이버시티 수신기법과 콘볼루션 부호화 기법을 각각 이용할 때의 광대역 DS-CDMA 시스템의 성능을 구하였다. 다중경로 페이딩으로는 라이시안 페이딩 채널을 가정하였고, 다중사용자간섭의 영향을 함께 분석하였다. 그리고 하이브리드 SC/MRC-L$_{c}$/L 다이버시티 기법과 론볼루션 부호화 기법을 채용하여 성능개선정도를 비교, 분석하였다. 하이브리드 SC/MRC-L$_{c}$/L 수신에서는 각각의 반송파에 대하여 상관을 취하고 상관기 출력들 중에서 가장 큰 신호성분을 L$_{c}$개만큼 선택하여 최대비 합성하며, 콘볼루션 부호화는 다중경로 페이딩 및 다중접속간섭에 의하여 발생된 오류를 정정 및 검출한다. 분석 결과, 콘볼루션 부호화의 경우는 부호이득과 전력제한 시스템의 trade off를 고려한 부호화율의 선택과 하이브리드 SC/MRC-L$_{c}$/L 수신의 경우, 다이버시티 가지의 증가는 선택의 폭이 커져 성능개선은 이루어지지만 가지의 배수가 동일할 경우 가지의 수가 적은 것이 시스템의 복잡성과 경제적인 면에서 효율적임을 알 수 있었다

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.19 no.6
• /
• pp.1115-1125
• /
• 1994

In this paper, an efficient concatenated coding scheme under the satellite channel is presented. The performance of this scheme in terms of bit error rate versus energy per information bit over white gaussian noise power density E/N has been evaluated via computer simulation as a function of various system parameters. To achieve accuracy in simulation results, the distortions caused from the satellite channel, such as the nonlinearity of the TWTA(traveling wave tube amplifier), signal distortions of the input and output filters, has been considered. The simulation results show that, through using the 2/3 punctured convolutional code as the inner code of the concatenated code system, the coding rate can be improved more over 16%, while maintaining the same system complexity and bit error performance.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.37 no.1
• /
• pp.76-87
• /
• 2000

Multicarrier DS-CDAM is an effective approach to realize wideband CDMA system in a multipath fading channeal. In this paper, we propose a cinvolutionally-coded overlapped multicarrier DS-CDMA system, and show the performance improvement by comparing with conventional multicarrier DS-CDMA system. We consider the case of 50% overlapping with the adjacent subband to utilize the transmission bandwidth more efficiently. In the proposed multicarrier system, each of the rate 1/M convolutionally-encoded symbols is also 1/R repetition coded and transmitted using overlapped multicarriers and we may obtain the coding gain and frequency diversity effect, simultaneously. We also analyze the possibility of reduction in total MUI by considering a raised-cosine wave-shaping filter having a roll-off factor (0< ${\beta}{\le}1$). It will be shown that the proposed system outperforms the multicarrier DS-CDMA system in $^{[3]}$.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.37 no.9
• /
• pp.11-23
• /
• 2000

Multicarrier DS-CDMA is an effective approach to realize wideband CDMA system in a multipath fading channel. In this paper, we propose a convolutionally-coded overlapped multicarrier DS-CDMA system, and analyze the performance with subband overlapping variation to determine the overlapping percentage showing best performance. Given a total number of subcarriers M*R, we will show that the BER variation is highly dependent on the rolloff factor P of raised-cosine chip wave-shaping filter irrespective of convolutional encoding rate I/M and repetition coding rate 1/R. We also analyze the possibility of reduction in total MUI by considering both variation of a rolloff factor (0 ($\beta$ :1) and variation of subband overlapping factor (0 ( A :2), and show that the proposed system may outperform the multicarrier DS-CDMA system in [1, 12].

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.23 no.11
• /
• pp.1355-1362
• /
• 1999

An experimental study on a double-concentric diffusion flame(DDF) has been carried on in order to Investigate the characteristics of soot formation compared to a normal coflow diffusion flame(NDF). Laser extinction technique has been used for an ethylene($C_2H_4$) and air flame with various flow rates. Soot formation In the double-concentric diffusion flame was enhanced by the inner inverse diffusion flame due to the increase in flame temperature and also suppressed due to the nitrogen-dilution from the inner air. Soot concentration at the flame axis of DDF was higher than that of the NDF, mainly because of the increase of temperature by inner flame. However, the maximum soot volume fraction of DDF was lower than NDF at the outer side of the flame, mainly due to the effect of nitrogen-dilution from the inner air.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.52 no.1
• /
• pp.51-54
• /
• 2003

The z-transform method is a basic mathematical tool in analyzing and designing digital signal processing systems for discrete input and output signals. There are may cases where the output signal is in the form of a discrete convolution sum of an input function and a designed digital processing algorithm function. It is well known that the z-transform of the convolution sum becomes the product of the two z-transforms of the input function and the digital processing function, whose proofs require the causality of the digital signal processing function in the almost all the available references. However, not all of the convolution sum functions are based on the causality. Many digital signal processing systems such as image processing system may depend not on the time information but on the spatial information, which has nothing to do with causality requirement. Thus, the application of the causality-based z-transform theorem on the convolution sum cannot be used without difficulty in this case. This paper proves the z-transform theorem on the discrete convolution sum without causality requirement, and make it possible for the theorem to be used in analysis and desing for any cases.

• Journal of the Korean Society of Radiology
• /
• v.16 no.3
• /
• pp.295-302
• /
• 2022

Sparse-view computed tomography (CT) imaging technique is able to reduce radiation dose, ensure the uniformity of image characteristics among projections and suppress noise. However, the reconstructed images obtained by the sparse-view CT imaging technique suffer from severe artifacts, resulting in the distortion of image quality and internal structures. In this study, we proposed a convolutional neural network (CNN) with wavelet transformation and residual learning for reducing artifacts in sparse-view CT image, and the performance of the trained model was quantitatively analyzed. The CNN consisted of wavelet transformation, convolutional and inverse wavelet transformation layers, and input and output images were configured as sparse-view CT images and residual images, respectively. For training the CNN, the loss function was calculated by using mean squared error (MSE), and the Adam function was used as an optimizer. Result images were obtained by subtracting the residual images, which were predicted by the trained model, from sparse-view CT images. The quantitative accuracy of the result images were measured in terms of peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The results showed that the trained model is able to improve the spatial resolution of the result images as well as reduce artifacts in sparse-view CT images effectively. Also, the trained model increased the PSNR and SSIM by 8.18% and 19.71% in comparison to the imaging model trained without wavelet transformation and residual learning, respectively. Therefore, the imaging model proposed in this study can restore the image quality of sparse-view CT image by reducing artifacts, improving spatial resolution and quantitative accuracy.

• Journal of Broadcast Engineering
• /
• v.24 no.1
• /
• pp.132-141
• /
• 2019

The necessity of transmitting video data over a narrow-bandwidth exists steadily despite that video service over broadband is common. In this paper, we propose a scalable video coding framework for low-resolution video transmission over a very narrow-bandwidth network by super-resolution of decoded frames of a base layer using a convolutional neural network based super resolution technique to improve the coding efficiency by using it as a prediction for the enhancement layer. In contrast to the conventional scalable high efficiency video coding (SHVC) standard, in which upscaling is performed with a fixed filter, we propose a scalable video coding framework that replaces the existing fixed up-scaling filter by using the trained convolutional neural network for super-resolution. For this, we proposed a neural network structure with skip connection and residual learning technique and trained it according to the application scenario of the video coding framework. For the application scenario where a video whose resolution is $352{\times}288$ and frame rate is 8fps is encoded at 110kbps, the quality of the proposed scalable video coding framework is higher than that of the SHVC framework.