• Proceedings of the Korea Multimedia Society Conference
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• 2002.05d
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• pp.896-900
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• 2002

본 논문에서는 기존의 워터마킹 알고리즘보다 채널에 대해서 더욱 강인한 특성을 위해 오류 정정 능력이 뛰어난 터보 부호 및 인간 시각 시스템을 이용한 디지털 워터마킹 방법을 제안하였다. 이 알고리즘에서는 터보 부호를 이용하여 워터마크를 생성하고, 채널에 강인한 특성을 위해 채널의 부가 정보를 이용하여 워터마크를 삽입한다. 제안한 워터마킹 알고리즘의 성능 평가를 위한 모의실험에서 제안한 워터마킹 알고리즘이 기존의 알고리즘보다 견고성면에서 우수함을 확인하였다.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.2
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• pp.6-14
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• 2007

In this paper, we propose and observe the Adaptive Modulation system with optimal Turbo Coded V-BLAST (Vertical-Bell-lab Layered Space-Time) technique that is applied the extrinsic information from MAP (Maximum A Posteriori) Decoder in decoding Algorithm of V-BLAST: ordering and slicing. The extrinsic information is used by a priori probability and the system decoding process is composed of the Main Iteration and the Sub Iteration. And comparing the proposed system with the Adaptive Modulation system using conventional Turbo Coded V-BLAST technique that is simply combined V-BLAST with Turbo Coding scheme, we observe how much throughput performance has been improved. In addition, we observe the proposed system using STD (Selection Transmit Diversity) scheme. As a result of simulation, Comparing with the conventional Turbo Coded V-BLAST technique with the Adaptive Modulation systems, the optimal Turbo Coded V-BLAST technique with the Adaptive Modulation systems has better throughput gain that is about 350 Kbps in 11 dB SNR range. Especially, comparing with the conventional Turbo Coded V-BLAST technique using 2 transmit and 2 receive antennas, the proposed system with STD (Selection Transmit Diversity) scheme show that the improvement of maximum throughput is about 1.77 Mbps in the same SNR range.

• 전자공학회논문지 IE
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• v.43 no.4
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• pp.115-121
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• 2006

In this paper, we proposed about data error check and correction on channel transmission in the communication system. LDPC codes are used for minimizing channel errors by modeling AWGN Channel as a VDSL system. Because LDPC Codes use low density parity bit, mathematical complexity is low and relating processing time becomes shorten. Also the performance of LDPC code is better than that of turbo code in long code word on iterative decoding algorithm. This algorithm is better than conventional algorithms to correct errors, the proposed algorithm assigns weights for errors concerning parity bits. The proposed weighted Bit-flipping algorithm is better than the conventional Bit-flipping algorithm and we are recognized improve gain rate of 1 dB.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.887-890
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• 2009

To transmit information over a channel in the presence of noise, there needs some technique to code the information. One of the coding techniques used for error detection and correction close to the Shannon limit is Low Density Parity Code. LDPC and decoding characteristic features by sum-product algorithm are matched for the performance to Turbo Code, RA(Repeat Accumulate) code, in case of very long code length of LDPC surpass their performance. This paper explains LDPC coding scheme of image data and decoding scheme, implements LDPC decoder in FPGA.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.39 no.11
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• pp.14-23
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• 2002

Two implementation methods for SOVA (Soft Output Viterbi Algorithm)of Turbo decoder are applied and verfied. The first method is the combination of a trace back (TB) logic for the survivor state and a double trace back logic for the weight value in two-step SOVA. This architecure of two-setp SOVA decoder allows important savings in area and high-speed processing compared with that of one-step SOVA decoding using register exchange (RE) or trace-back (TB) method. Second method is adjusting the reliability value with a scaling factor between 0.25 and 0.33 in order to compensate for the distortion for a rate 1/3 and 8-state SOVA decoder with a 256-bit frame size. The proposed schemes contributed to higher SNR performance by 2dB at the BER 10E-4 than that of SOVA decoder without a scaling factor. In order to verify the suggested schemes, the SOVA decoder is testd using Xillinx XCV 1000E FPGA, which runs at 33.6MHz of the maximum speed with 845 latencies and it features 175K gates in the case of 256-bit frame size.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.6 s.360
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• pp.40-47
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• 2007

In this paper, we propose and analyze the Adaptive Modulation System with optimal Turbo Coded V-BLAST(Vertical-Bell-lab Layered Space-Time) technique that adopts the extrinsic information from MAP (Maximum A Posteriori) Decoder with Iterative Decoding as a priori probability in two decoding procedures of V-BLAST; the ordering and the slicing. Also, we consider and compare the Adaptive Modulation System using conventional Turbo Coded V-BLAST technique that is simply combined V-BLAST with Turbo Coding scheme and the Adaptive Modulation System using conventional Turbo Coded V-BLAST technique that is decoded by the ML (Maximum Likelihood) decoding algorithm. We observe a throughput performance and a complexity. As a result of a performance comparison of each system, it has been proved that the complexity of the proposed decoding algorithm is lower than that of the ML decoding algorithm but is higher than that of the conventional V-BLAST decoding algorithm. however, we can see that the proposed system achieves a better throughput performance than the conventional system in the whole SNR (Signal to Noise Ratio) range. And the result shows that the proposed system achieves a throughput performance close to the ML decoded system. Specifically, a simulation shows that the maximum throughput improvement in each MIMO scheme is respectively about 350 kbps, 460 kbps, and 740 kbps compared to the conventional system. It is suggested that the effect of the proposed decoding algorithm accordingly gets higher as the number of system antenna increases.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.344-352
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• 2020

Covertness and performance are very important design goals in the underwater communications. To satisfy both of them, we proposed efficient underwater communication model which combined multiband and direct sequence spread spectrum method in order to improve performance and covertness simultaneously. Turbo coding method with 1/3 coding rates is used for channel coding algorithm, and turbo equalization method which iterately exchange probabilistic information between equalizer and decoder is used for receiver side. After optimal threshold value was set in Rake processing, this paper analyzed the performance by varying the number of chips were 8, 16, 32 and the number of bands were from 1 to 4. Through the simulation results, we confirmed that the performance improvement was obtained by increasing the number of bands and chips. 2~3 dB of performance gain was obtained when the number of chips were increased in same number of bands.

• The Journal of the Acoustical Society of Korea
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• v.41 no.4
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• pp.410-418
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• 2022

Channel reliability estimation for iterative codes such as turbo codes is very important factor in time varying underwater acoustic channel, an incorrect estimation of channel reliability induced performance degradation. Therefore, this paper presents an optimal channel reliability estimation method for turbo coded FSK signal with rate of 1/3. The estimated BER algorithm is a method that can estimate the reliability of received data by comparing received data and decoded data, and we determine optimal channel reliability by using the method. In order to analyze the performance, the experiment was conducted on a lake in Munkyeong city by moving in the range of 300 m to 500 m. At the result of applying presented method to failed decoding packets, we confirm all packets are decoded successfully.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.4
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• pp.569-574
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• 2017

In order to transmit information in a channel environment in which noise exists, a coding technique of information is required. One of the coding techniques used for error detection and correction close to the Shannon limit is Low Density Parity Code(LDPC). LDPC and decoding characteristic features by Sum-product algorithm are matched for the performance to Turbo Code, RA(Repeat Accumulate) code, in case of very long code length of LDPC surpass their performance. This paper explains LDPC coding scheme of image data and decoding scheme, implements LDPC decoder in FPGA.

• Journal of Internet Computing and Services
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• v.8 no.4
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• pp.61-70
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• 2007

In this paper, we propose and observe the Adaptive Modulation system with optimal Turbo Coded V-BLAST(Vertical-Bell-lab Layered Space-Time) technique that is applied the extrinsic information from MAP Decoder in decoding Algorithm of V-BLAST: ordering and slicing. And comparing the proposed system with the Adaptive Modulation system using conventional Turbo Coded V-BLAST technique that is simply combined V-BLAST with Turbo Coding scheme, we observe how much throughput performance and SNR has been improved. In addition, we show that the proposed system using STD(Selection Transmit Diversity) scheme results in on improved result, By using simulation and comparing to conventional Turbo Coded V-BLAST technique with the Adaptive Modulation systems, the optimal Turbo Coded V-BLAST technique with the Adaptive Modulation systems has SNR gain over all SNR range and better throughput gain that is about 350Kbps in 11dB SNR range. Also, comparing with the conventional Turbo Coded V-BLAST technique using 2 transmit and 2 receive antennas, the proposed system with STD scheme show that the improvement of maximum throughput is about 1.77Mbps in the same SNR range and the SNR gain is about 5.88dB to satisfy 4Mbps throughput performance.