• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.774-777
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• 2005

In this paper, we propose performance improvement algorithm for high data rate wireless personal area network (HDR-WPAN) system using turbo code. Turbo code increase detection delay and computation according to iterate counts. However, turbo code has been shown to be very close th the Shanon limit, can be classified as a block-based error correction code. Turbo code has gain about E$_b$/N$_o$=5.8dB at 10$^{-4}$ in the multipath indoor channel. In the result, HDR-WPAN system adopted turbo code has reliable communication by low power.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.6
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• pp.1184-1189
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• 2001

In this paper was analyzed the performance of turbo code using semi-random interleaver which proposed a reference numbers 11. Which was analyzed comparison the performance of between the current mobile communication system had been used the viterbe decoding algorithm of convolutional code and turbo codes when fixed constraint length. The result was defined that the performance of turbo code rose a $E_{b/}$ $N_{o}$=4.7[㏈] than convolutional code, when convolutional code and turbo code was fixed by BER = 10$^{-4}$ and constraint length K 5.5.5.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.21-27
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• 2013

In this paper, we propose a low-complexity Turbo coded BICM-ID (bit-interleaved coded modulation with iterative decoding) system. A Turbo code is a powerful error correcting code with a BER (bit error rate) performance very close to the Shannon limit. In order to increase spectral efficiency of the Turbo code, a coded modulation combining Turbo code with high order modulation is used. The BER performance of Turbo-BICM can be improved by Turbo-BICM-ID using iterative demodulation and decoding algorithm. However, compared with Turbo-BICM, the decoding complexity of Turbo-BICM-ID is increased by exchanging information between decoder and demodulator. To reduce the decoding complexity of Turbo-BICM-ID, we propose a low-complexity Turbo-BICM-ID system. When compared with conventional Turbo-BICM-ID, the proposed scheme not only show similar BER performance but also reduce the decoding complexity.

• Proceedings of the IEEK Conference
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• 2000.11b
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• pp.273-276
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• 2000

Recently, Turbo code has been considered for channel coding in IMT-2000(International Mobile Telecommunication-2000) system, because it offers better error correcting capability than the traditional convolution/viterbi coding . In this paper, a turbo code decoder for speech transmission in IMT-2000 system with frame size 192 bits, constrait length K=3, generator polynomials G(5,7) and code rate R=1/3 is designed using SOVA(Soft Output Viterbi Algorithm) and block interleaver

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.8
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• pp.1613-1619
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• 2004

Turbo codes of long block sizes have been known to show very good performance in an AWGN channel and the turbo code has been strongly recommended as error correction code for W-CDMA in 3GPP(3rd Generation Partnership Project). Recently, turbo codes of short block sizes suitable for real time communication systems have attracted a lot of attention. Thus, in this paper we consider the turbo code of 1/3 code rate and short frame size of 192 bits in ITU-R channel model. We analyzed the performance of W-CDMA systems of 10MHz bandwidths employing RAKE receiver with not only MRC diversity but also SOVA-based turbo code.

• Journal of Broadcast Engineering
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• v.16 no.6
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• pp.1026-1035
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• 2011

This paper presents generalization and application for the conventional SISO decoding algorithm of Block Turbo Codes. R. M. Pyndiah suggested an iterative SISO decoding algorithm for Product Codes, two-dimensionally combined linear block codes, on AWGN channel. It wascalled Block Turbo Codes. Based on decision of Chase algorithm which is SIHO decoding method, SISO decoder for BTC computes soft decision information and transfers the information to next decoder for iterative decoding. Block Turbo Codes show Shannon limit approaching performance with a little iteration at high code rate on AWGN channel. In this paper we generalize the conventional decoding algorithm of Block Turbo Codes, under BPSK modulation and AWGN channel transmission assumption, to the LLR value based algorithm and suggest an application example such as concatenated structure of LDPC codes and Block Turbo Codes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3C
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• pp.306-313
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• 2007

In this paper, we efficiently implemented turbo code algorithm in FPGA H/W(hardware) resource. The used turbo code algorithm has the characteristics; the size of constraint is 3, encoder type is 1/3, the size of random interleaver is 2048. The proposed H/W consists of MAP block for calculating alpha and delta using delta value, storing buffer for each value, multiplier for calculating lamda, and lamda buffer. The proposed algorithm and H/W architecture was verified by C++ language and was designed by VHDL. Finally the designed H/W was programmed into FPGA and tested in wireless communication environment for field availability. The target FPGA of the implemented H/W is VERTEX4 XC4VFX12-12-SF363 and it is stably operated in 131.533MHz clock frequency (7.603ns).

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.1
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• pp.116-126
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• 2000

Turbo codes are the most exciting and potentially important development in coding theory in recent years. They were introduced in 1993 by Berrou, Glavieux and $Thitimajshima,({(1)}$ and claimed to achieve near Shannon-limit error correction performance with relatively simple component codes and large interleavers. A required Eb/N0 of 0.7㏈ was reported for BER of $10^{-5}$ and code rate of $l/2.^{(1)}$ However, to implement the turbo code system, there are various important details that are necessary to reproduce these results such as AGC gain control, optimal wordlength determination, and metric rescaling. Further, the memory required to implement MAP-based turbo decoder is relatively considerable. In this paper, we confirmed the accuracy of these claims by computer simulation considering these points, and presented a optimal wordlength for Turbo code design. First, based on the analysis and simulation of the turbo decoder, we determined an optimal wordlength of Turbo decoder. Second, we suggested the MAP decoding algorithm based on sliding-window method which reduces the system memory significantly. By computer simulation, we could demonstrate that the suggested fixed-point Turbo decoder operates well with negligible performance loss.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10C
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• pp.758-763
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• 2008

We introduce a noise-predictive turbo equalization using noise filter in perpendicular magnetic recording(PMR) channel. The noise filter mitigates the colored noise in high-density PMR channel. In this paper, the channel detectors used are SOVA (Soft Output Viterbi Algorithm) and BCJR algorithm which proposed by Bahl et al., and the outer decoder used is LDPC (Low Density Parity Check) code that is implemented by sum-product algorithm. Two kinds of LDPC codes are experimented. One is the 0.5Kbyte (4336,4096) LDPC code with the code rate of 0.94, and the other is 1Kbyte (8432,8192) LDPC code with the code rate of 0.97.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.1095-1102
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• 2016

In this paper, we propose a decoding scheme that can apply to a three dimensional turbo product code(TPC) with a single parity check code(SPC). In general, SPC is used an axis with shortest code length in order to maximize a code rate of the TPC. However, SPC does not have any error correcting capability, therefore, the error correcting capability of the three-dimensional TPC results in little improvement in comparison with the two-dimensional TPC. We propose two schemes to improve performance of three dimensional TPC decoder. One is $min^*$-sum algorithm that has advantages for low complexity implementation compared to Chase-Pyndiah algorithm. The other is a modified serial iterative decoding scheme for high performance. In addition, the simulation results for the proposed scheme are shown and compared with the conventional scheme. Finally, we introduce some practical considerations for hardware implementation.