• Proceedings of the IEEK Conference
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• 2000.06a
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• pp.5-8
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• 2000

In this paper, we present a new cぉnet coding method, so called MLC (Multi-Level Codes), for error detection and correction in digital wireless communication. MLC coding method we the same coding procedure wed in the convolutional coding but it is distinguished from the existing convolutional coding in point of generating the code word by using multi-level information data (M-ary signal) and in point of speed of coding procedure Through computer simulation, we analyze the performance of the coding method suggested here compared to convolutional coding method in case of modulo-operation and in case of non-binary coding Procedure respectively under various channel environments.

• Proceedings of the IEEK Conference
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• 2000.06a
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• pp.17-20
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• 2000

This paper addresses a novel algorithm for variable rate channel coding with interleaver punctured convolutional code for wireless communication. In other to increase the coding performance and achieve the variable channel coding rate, serially concatenated convolutional coding scheme will be applied. In this paper, we characterize the effect of interleaver puncturing on the effectiveness of the proposed scheme some simulation results are presented, in which the channel model of additive Gaussian noise is assumed.

• The Journal of the Korea Contents Association
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• v.10 no.9
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• pp.88-96
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• 2010

We propose the efficient channel coding method combined with a 2.4kbps speech coder. The code rate of a channel coder is given by 1/2 and 1/2 rate convolutional coder is obtained from the punctured convolutional coder with rate of 1/3. The punctured convolutional coder is used for a variable rate allocation. The puncturing method according to the importance of the output data of the source encoder is applied for the convolutional coder. The importance of output data is analyzed by evaluating the bit error sensitivity of speech parameter bits. The performance of proposed coder is analyzed and simulated in Rayleigh fading channel and AWGN channel. The experimental results with 2.4kbps EHSX coder show that the variable rate channel coding method is superior to non-variable channel coding method from the subjective speech quality.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.11-14
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• 2018

The aim of this study is to rectify the misclassified image features and enhance the performance of image classification tasks by incorporating a channel- coding technique, widely used in telecommunication. Specifically, the proposed algorithm employs the error - correcting mechanism of convolutional coding combined with the convolutional neural networks (CNNs) that are the state - of- the- arts image classifier s. We develop an encoder and a decoder to employ the error - correcting capability of the convolutional coding. In the encoder, the label values of the image data are converted to convolutional codes that are used as target outputs of the CNN, and the network is trained to minimize the Euclidean distance between the target output codes and the actual output codes. In order to correct misclassified features, the outputs of the network are decoded through the trellis structure with Viterbi algorithm before determining the final prediction. This paper demonstrates that the proposed architecture advances the performance of the neural networks compared to the traditional one- hot encoding method.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1986.04a
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• pp.1-3
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• 1986

We are concerned with transmitting numerical source data of {0, 1, 2, ..., 2k-1} through a channel coding system. The rate 1/v dual-k convolutional code with the orthogonal MFSK modulation and the Viterbl decoding is employed for the implementation of the channel coding system. The mean square error of the dual-k convolutional code is evaluated for the numerical source transmitted over an additive white Gaussian noise channel with Rayleigh fading.

• Journal of Communications and Networks
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• v.1 no.3
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• pp.182-188
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• 1999

The optimal joint maximum-likelihood sequence estima-for using an array of antennas is derived for synchronous direct sequence-code division multiple access (DS-CDMA) system. Each user employs a rate 1/n convolutional code for channel coding for the additive white Gaussian noise (AWGN) channel. The array re-ceiver structure is composed of beamformers in the users' direc-tions followed by a bank of matched filters. The decoder is imple-mented using a Viterbi algorithm whose states depend on the num-ber of users and the constraint length of the convolutional code. The asymptotic array multiuser coding gain(AAMCG)is defined to encompass the asymptotic multiuser coding gain and the spatial information on users' locations in the system. We derive the upper and lower bounds of the AAMCG. As an example, the upper and lower bounds of AAMCG are obtained for the two user case where each user employes the maximum free distance convolutional code with rate 1/2. The enar-far resistance property is also investigated considering the number of antenna elements and user separations in the space.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.19-22
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• 1998

In this study, the efficient channel coding method combined with CS-ACELP is proposed. The same convolutional coder and Viterbi decoder of COMA mobile communication system is used as channel coder. To make the best available use of limited channel coding redundancy, unequal error protection of punctured convolutional coder is used for variable reate allocation. But, the overall code rate is given by 2. The performance of proposed coder is analyzed and simulated in a Rayleigh fading channel. Experimental results show that the objective and subjective speech quality of variable rate channel coding methods are superior to those of non-variable channel coding method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.8A
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• pp.1437-1440
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• 2001

We present a modification method for runlength limited codes based on convolutional codes. This method is based on cosets of convolutional codes and can be applied to any convolutional code without degradation of error control performance of the codes. The upper bound of maximum zero and/or one runlength are provided. Some convolutional codes which have the shortest maximum runlength for given coding parameters are tabulated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.6
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• pp.1115-1125
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• 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 Broadcast Engineering
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• v.24 no.1
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• pp.132-141
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• 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.