• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.11
• /
• pp.2465-2473
• /
• 2012

Recently, as one of low complexity video encoding methods, DVC (Distributed Video Coding) scheme has been actively studied. Most of DVC schemes exploit feedback channel to achieve better coding performances, however, this causes these schemes to have high decoding delay. In order to overcome these, this paper proposes a new fast DVC decoding method using parity-bit request model, which can be obtained by using bit-error rate, sent by encoder with motion vector, which is transmitted through feedback channel by decoder after generating side information. Through several simulations, it is shown that the proposed method improves greatly the decoding speed, compared to the conventional schemes.

• Journal of Communications and Networks
• /
• v.7 no.3
• /
• pp.243-247
• /
• 2005

We propose an efficient block least-mean-square (BLMS) adaptive algorithm, in conjunction with error control coding, for direct-sequence code division multiple access (DS-CDMA) systems. The proposed adaptive receiver incorporates decision feedback detection and channel encoding in order to improve the performance of the standard LMS algorithm in convolutionally coded systems. The BLMS algorithm involves two modes of operation: (i) The training mode where an uncoded training sequence is used for initial filter tap-weights adaptation, and (ii) the decision-directed where the filter weights are adapted, using the BLMS algorithm, after decoding/encoding operation. It is shown that the proposed adaptive receiver structure is able to compensate for the signal-to­noise ratio (SNR) loss incurred due to the switching from uncoded training mode to coded decision-directed mode. Our results show that by using the proposed adaptive receiver (with decision feed­back block adaptation) one can achieve a much better performance than both the coded LMS with no decision feedback employed. The convergence behavior of the proposed BLMS receiver is simulated and compared to the standard LMS with and without channel coding. We also examine the steady-state bit-error rate (BER) performance of the proposed adaptive BLMS and standard LMS, both with convolutional coding, where we show that the former is more superior than the latter especially at large SNRs ($SNR\;\geq\;9\;dB$).

• Journal of IKEEE
• /
• v.10 no.1 s.18
• /
• pp.69-74
• /
• 2006

In this paper, we present symbol detection methods for decision feedback equalizers (DFE) in trellis coded modulation systems. The proposed symbol detectors improve symbol error rate (SER) by exploiting the coding structure of trellis coded modulation (TCM). For example, for 8-PAM signals the achieved SER with the proposed detection scheme is improved to $2{\times}10^{-5}$ from $2.5{\times}10^{-2}$ of the conventional symbol-by-symbol detector under AWGN channel at 20dB SNR. This SER improvements mitigate error propagation of DFE.and produces significant over-all SER improvement for under multipath channels (for example, from 0.26 to 0.01 and 0.005 under a severe multipath channel 20dB SNR as shown in the simulation result of this paper).

• Nuclear Engineering and Technology
• /
• v.48 no.3
• /
• pp.660-672
• /
• 2016

In Part I of this paper, the two-temperature homogenized model for the fully ceramic microencapsulated fuel, in which tristructural isotropic particles are randomly dispersed in a fine lattice stochastic structure, was discussed. In this model, the fuel-kernel and silicon carbide matrix temperatures are distinguished. Moreover, the obtained temperature profiles are more realistic than those obtained using other models. Using the temperature-dependent thermal conductivities of uranium nitride and the silicon carbide matrix, temperature-dependent homogenized parameters were obtained. In Part II of the paper, coupled with the COREDAX code, a reactor core loaded by fully ceramic microencapsulated fuel in which tristructural isotropic particles are randomly dispersed in the fine lattice stochastic structure is analyzed via a two-temperature homogenized model at steady and transient states. The results are compared with those from harmonic- and volumetric-average thermal conductivity models; i.e., we compare $k_{eff}$ eigenvalues, power distributions, and temperature profiles in the hottest single channel at a steady state. At transient states, we compare total power, average energy deposition, and maximum temperatures in the hottest single channel obtained by the different thermal analysis models. The different thermal analysis models and the availability of fuel-kernel temperatures in the two-temperature homogenized model for Doppler temperature feedback lead to significant differences.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.6
• /
• pp.1914-1925
• /
• 2014

Inter-symbol interference (ISI) problem is inevitable when the guard interval (GI) is shorter than the delay spread (DS) for an orthogonal frequency division multiplexing (OFDM) system. Iterative techniques have been proposed to overcome such a problem. However, most of existing algorithms are not efficient for an OFDM system with a small GI working under the channel with a large DS. Especially in the case of the DS spans a longer time than the half of the OFDM symbol duration. On the other hand, conventional algorithms, which can reduce the effects of the severe ISI, often employ several impractical assumptions to support the conclusions. In this paper, we present a robust decision feedback equalizer (DFE) for the OFDM system to overcome the severe ISI problem. The proposed DFE removes the ISI in a same manner as the residual inter-symbol interference cancellation (RISIC) algorithm. However, the inter-carrier interference (ICI) is reduced via cyclicity removal instead of the cyclicity restoration used in the conventional algorithms. The link-level simulation (LLS) results indicate that our proposed DFE scheme can dramatically improve the BER performance when the DS spans longer than the half of ODFM symbol duration.

• Journal of the Korea Society of Computer and Information
• /
• v.7 no.2
• /
• pp.95-100
• /
• 2002

By feedback channel, the decoder reports the addresses of corrupted macroblocks induced by transmission errors back to the encoder With these negative acknowledgements, the encoder can make the next frame having propagated errors by using forward dependency based on GOBs and MBs of the frame happening transmission errors. The encoder can precisely calculate and track the propagated errors by examining the backward motion dependency for each of four comer pixels in the current encoding frame until before-mentioned the next frame. The error-propagation effects can be terminated completely by INTRA refreshing the affected macroblocks. Such a fast algorithm further reduce the computation and memory requirements. The advantages of the low computation complexity and the low memory requirement are Particularly suitable for real-time implementation.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.41 no.9
• /
• pp.39-45
• /
• 2004

A design method is proposed for the sequence detection with fixed decision delay with less hardware complexity using the concept of the Voronoi diagram and its dual, the Delaunay tessellation. This detector design is based on the Fixed Delay Tree Search (FDTS) detection. The FDTS is a computationally efficient sequence detection algerian and has been shown to achieve near-optimal performance in the severe Intersymbol Interference (ISI) channels when combined with decision feedback equalization and the appropriate channel coding. In this approach, utilizing the information contained in the Voronoi diagram or equivalently the Delaunay tessellation, the relative location of the detector input sequence in the multi-dimensional Euclidean space is found without any computational redundancy, which leads to a reduced complexity implementation of the detector.

• Journal of Broadcast Engineering
• /
• v.12 no.6
• /
• pp.641-648
• /
• 2007

The decoding structure of up-to-date ATSC DTV receivers is well optimized, and it seems that 14.6 dB is the unbreakable minimum SNR in the AWGN channel. But the SNR satisfying the Shannon capacity of DTV receivers is 11.76 dB, So, the SNR gab between the 14.6 dB and the 11.76 dB is about 2.8 dB. In order to approach the Shannon capacity we propose a recursive trellis decoder which uses reliable feedback data obtained by an RS decoder. The performance enhancement of about 0.8 dB can be achieved in case of the AWGN channel.

• The Journal of Korean Institute for Practical Engineering Education
• /
• v.1 no.1
• /
• pp.44-50
• /
• 2009

Virtual reality is a technology for enabling users to interact with a computer generated environment which can be similar to the real world. A multi-channel display is one of the virtual reality platform for creating a high resolution image. In this paper, we develop a multi-channel display system which allows users to immersively understand the 3D educating contents and furthermore, we construct 3D educating contents for describing a semiconductor concept and process.

• Journal of Institute of Control, Robotics and Systems
• /
• v.9 no.11
• /
• pp.917-924
• /
• 2003

Recurrent neural networks have been successfully applied to communications channel equalization. Major disadvantages of gradient-based learning algorithms commonly employed to train recurrent neural networks are slow convergence rates and long training sequences required for satisfactory performance. In a high-speed communications system, fast convergence speed and short training symbols are essential. We propose decision feedback equalizers using a recurrent neural network trained with Kalman filtering algorithms. The main features of the proposed recurrent neural equalizers, utilizing extended Kalman filter (EKF) and unscented Kalman filter (UKF), are fast convergence rates and good performance using relatively short training symbols. Experimental results for two time-varying channels are presented to evaluate the performance of the proposed approaches over a conventional recurrent neural equalizer.