• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.4
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• pp.430-435
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• 2018

In this paper, an improved decoding scheme for low-complexity parity-check(LCPC) code with small code length is proposed. The LCPC code is less complex than the turbo code or low density parity check(LDPC) code and requires less memory, making it suitable for communication between internet-of-things(IoT) devices. The IoT devices are required to have low complexity due to limited energy and have a low end-to-end delay time. In addition, since the packet length to be transmitted is small and the signal processing capability of the IoT terminal is small, the LCPC coding system should be as simple as possible. The LCPC code can correct all single errors and correct some of the two errors. In this paper, the proposed decoding scheme improves the bit error rate(BER) performance without increasing the complexity by correcting both errors using the soft value of the modulator output stage. As a result of the simulation using the proposed decoding scheme, the code gain of about 1.1 [dB] was obtained at the bit error rate of $10^{-5}$ compared with the existing decoding method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5C
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• pp.498-504
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• 2009

A high-performance low-complexity decoding algorithm for LDPC codes is proposed in this paper, which has the advantages of both bit-flipping (BF) algorithm and sum-product algorithm (SPA). The proposed soft bit-flipping algorithm requires only simple comparison and addition operations for computing the messages between bit and check nodes, and the amount of those operations is also small. By increasing the utilization ratio of the computed messages and by adopting nonuniform quantization, the signal-to-noise ratio (SNR) gap to the SPA is reduced to 0.4dB at the frame error rate of 10-4 with only 5-bit assignment for quantization. LDPC codes with high column or row weights, which are not suitable for the SPA decoding due to the complexity, can be practically implemented without much worsening the error performance.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1996.06a
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• pp.554-556
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• 1996

• Journal of IKEEE
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• v.4 no.2 s.7
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• pp.257-265
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• 2000

Turbo Code decoder is an iterate decoding technology, which extracts extrinsic information from the bit to be decoded by calculating both forward and backward metrics in each decoding step, and uses the information to the next decoding step. Viterbi decoder, which is for a convolutional code, runs continuous mode, while Turbo Code decoder runs by block unit. There are algorithms used in a decoder : which are MAP(maximum a posteriori) algorithm requiring very complicated calculation and SOVA(soft output Viterbi algorithm) using Viterbi algorithm suggested by Hagenauer, and it is known that the decoding performance of MAP is better. The result of this make experimentation shows that the performance of SOVA, which has half complex algorithm compare to MAP, is almost same as the performance of MAP when the SOVA decoding performance is supplemented with Robust equalization techniques.

• Journal of Communications and Networks
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• v.17 no.4
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• pp.351-361
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• 2015

In this paper, a new decoding scheme is proposed to improve the error correcting performance of low-density parity-check (LDPC) codes in high signal-to-noise ratio (SNR) region by using post-processing. It behaves as follows: First, a conventional LDPC decoding is applied to received LDPC codewords one by one. Then, we count the number of word errors in a predetermined number of decoded codewords. If there is no word error, nothing needs to be done and we can move to the next group of codewords with no delay. Otherwise, we perform a proper post-processing which produces a new soft-valued codeword (this will be fully explained in the main body of this paper) and then apply the conventional LDPC decoding to it again to recover the unsuccessfully decoded codewords. For the proposed decoding scheme, we adopt a simple product code structure which contains LDPC codes and simple algebraic codes as its horizontal and vertical codes, respectively. The decoding capability of the proposed decoding scheme is defined and analyzed using the parity-check matrices of vertical codes and, especially, the combined-decodability is derived for the case of single parity-check (SPC) codes and Hamming codes used as vertical codes. It is also shown that the proposed decoding scheme achieves much better error correcting capability in high SNR region with little additional decoding complexity, compared with the conventional LDPC decoding scheme.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.46-49
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• 2010

최근의 iterative detection and decoding (IDD) 기법에서의 soft 복호화방식은, log-likelihood ratio (LLR) 값의 신뢰도를 높이기 위해 기존의 구복호화 (sphere decoding) 방식보다는 리스트를 형성하는 구복호화방식 (list sphere decoding : LSD)이 대두되고 있다. 기존의 구복호화 방식과는 달리 리스트 구복호화 방식은 그 성능의 우수함에도 불구하고, 여러 격자 포인트들을 검출해야 하므로 신호대잡음비 (signal-to-noise ratio : SNR) 의 증가에 따른 복잡도의 이득을 거의 취할 수 없을 뿐만 아니라, 무엇보다 신뢰도가 높은 LLR 값을 얻는 데에 영향이 작은 포인트를 검출하는 경우도 생긴다는 점에서 비효율적인 측면이 있다. 이에 본 논문에서는 리스트 구복호화 검출방식의 효율성을 높이기 위해 LLR 값에 적은 영향을 미치는 격자 포인트들을 제거하는 방식에 대해 연구하였다. 본 연구의 목표는 MIMO 시스템에서의 기존의 리스트 구복호화 기법의 capacity와 실제 성능과 최대한 유사한 성능을 내면서도 그 복잡도를 현저히 줄이는 것이며, 구체적으로는 검출을 위한 초기 구반경의 최적화를 기반으로 한다.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.61-64
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• 1999

The turbo code appropriate to IMT-2000 is known to have a good performance whenever the size of frame increases. But it is not appropriate to a sort of video service to need real time because of decoding complexity and long delay time by the size of frame. Therefore this paper proposes decoding decision algorithm of short frame in which soft output is weighted according to iteration number in turbo decoder. Performance of the proposed algorithm is analysed in the AWGN channel when short length of frame is 100, 256, 640. As the result. it is appeared that the proposed decoding decision algorithm has improved in BER other than in the existing MAP decoding algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.7
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• pp.1419-1426
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• 1997

A new SCEE(Syndrome Check Error Estimation) decoding method for convolutional code and concatenated SCEE/RS (Reed-Solomon) conding scheme are proposed. First, we describe the operation of the decoding steps in the proposed algorithm. Then deterministic values on the decoding operation are drived when some combination of predecoder-reencoder is used. Computer simulation results show that the compuatational complexity of the proposed SCEE decoder is significantly reduced compared to that of conventional Viterbi-decoder without degratation of the $P_{e}$ performance. Also, the concatenated SCEE/RS decoder has almost the same complexity of a RS decoder and its coding gain is higher than that of soft decision Viterbi or RS decoder respectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.399-401
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• 2013

In this paper, we present the method to impove the performance by using iterative decoding in LDPC codes with 8-PSK modulation. Iterative decoding is the technique that improve the performance after the input signals of receiver are re-calculated by using the soft decision output of decoder. DVB-S2 system with 8-PSK modulation based on iterative decoding had a better performance than DVB-S2 with 8-PSK modulation over Gaussian channels.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.478-481
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• 2000

In this paper, we propose a joint coding system for still images using source coding and powerful error correcting code schemes. Our system comprises an LVQ (lattice vector quantization) source coding for wavelet transformed images and turbo coding for channel coding. The parameters of the image encoder and channel encoder have been optimized for an n-D (dimension) cubic lattice (D$_{n}$, Z$_{n}$), parallel concatenation fur two simple RSC (recursive systematic convolutional code) and an interleaver. For decoding the received image in the case of the AWGN (additive white gaussian noise) channel, we used an iterative joint source-channel decoding algorithm for a SISO (soft-input soft-output) MAP (maximum a posteriori) module. The performance of transmission system has been evaluated in the PSNR, BER and iteration times. A very small degradation of the PSNR and an improvement in BER were compared to a system without joint source-channel decoding at the input of the receiver.ver.