• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.5
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• pp.31-40
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• 2010

This paper describes a LDPC decoder for IEEE 802.11n wireless LAN standard. The designed processor supports parity check matrix for block length of 1,944 and code rate of 1/2 in IEEE 802.11n standard. To reduce hardware complexity, the min-sum algorithm and layered decoding architecture are adopted. A novel memory reduction technique suitable for min-sum algorithm was devised, and our design reduces memory size to 25% of conventional method. The LDPC decoder processor synthesized with a $0.35-{\mu}m$ CMOS cell library has 200,400 gates and memory of 19,400 bits, and the estimated throughput is about 135 Mbps at 80 MHz@2.5v. The designed processor is verified by FPGA implementation and BER evaluation to validate the usefulness as a LDPC decoder.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.3
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• pp.51-56
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• 2005

To improve the BER of OFDM on a fading channel, a low-density parity check coded OFDM system is proposed in this paper. LDPC codes are decoded with Sum-Product or Belief Propagation Algorithm known by probability propagation algorithm. When LDPC codes are applied to OFDM system, the BER performance is dependant on the iteration number of decoding. To improve the spectral efficiency, multi-level modulations are used in mobile communication system. But, It is not clear how to decode LDPC code used in OFDM with multi-level modulations. In the paper, a decoding algorithm is described for LDPC coded OFDM with MPSK. When use the proposed decoding algorithm, we get the good BER for AWGN and a Fading Channel. Simulation results show that the proposed decoding algorithm is confirmed LDPC coded OFDM with MPSK.

• 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.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.4
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• pp.48-58
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• 2016

This paper presents the high-throughput fully-parallel architecture for GF(64) (160,80) regular (2,4) non-binary LDPC (NB-LDPC) codes decoder based on the extended min sum algorithm. We exploit the NB-LDPC code that features a very low check node and variable node degree to reduce the complexity of decoder. This paper designs the fully-parallel architecture and allows the interleaving check node and variable node to increase the throughput of the decoder. We further improve the throughput by the proposed early sorting to reduce the latency of the check node operation. The proposed decoder has the latency of 37 cycles in the one decoding iteration and achieves a high throughput of 1402Mbps at 625MHz.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.2
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• pp.37-43
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• 2008

The performance and hardware complexity of LDPC decoders depend on the design parameters of quantization, the clipping threshold $c_{th}$ and the number of quantization bits q, and also on the maximum number of decoding iterations. In this paper, the BER performances of LDPC codes are evaluated according to the clipping threshold $c_{th}$ and the number of quantization bits q through the simulation studies. By comparing the quantized Min-Sum algorithm with the ideal Min-Sum algorithm, it is shown that the quantized case with $c_{th}=2.5$ and q=6 has the best performance, which approaches the idea case. The decoding complexities are calculated and the word error rates(WER) are estimated by using the pdf which is obtained through the statistical analyses on the iteration numbers. These results can be utilized to tradeoff between the decoding performance and the complexity in LDPC decoder design.

• JSTS:Journal of Semiconductor Technology and Science
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• v.13 no.1
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• pp.8-14
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• 2013

A low density parity check (LDPC) decoder provides a most powerful error control capability for mobile communication devices and storage systems, due to its performance being close to Shannon's limit. In this paper, we introduce an efficient overlapped LDPC decoding algorithm using a upper dual-diagonal parity check matrix structure. By means of this algorithm, the LDPC decoder can concurrently execute parts of the check node update and variable node update in the sum-product algorithm. In this way, we can reduce the number of clock cycles per iteration as well as reduce the total latency. The proposed decoding structure offers a very simple control and is very flexible in terms of the variable bit length and variable code rate. The experiment results show that the proposed decoder can complete the decoding of codewords within 70% of the number of clock cycles required for a conventional non-overlapped decoder. The proposed design also reduces the power consumption by 33% when compared to the non-overlapped design.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.4
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• pp.11-16
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• 2004

A simple stopping criterion for iterative decoding based on min-sum processing is presented. While most stopping criteria suggested in the literature, are based on Cross Entropy (CE) and its simplification, the proposed stopping criterion is to check if a decoded sequence is a valid codeword along the encoder trellis structure. This new stopping criterion requires less computational complexity and saves mem4)ry compared to the conventional stopping rules. The numerical results are presented on the 3GPP turbo code and a Serially Concatenated Convolutional Cods (SCCC).

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.3
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• pp.226-231
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• 2010

This paper proposes a new coding technique for constructing error correcting high rate DC-free multimode code using a generator matrix generated from a sparse parity-check matrix. The scheme exploits high rate generator matrixes for producing distinct candidate codewords. The decoding complexity depends on whether the syndrome of the received codeword is zero or not. If the syndrome is zero, the decoding is simply performed by expurgating the redundant bits of the received codeword. Otherwise, the decoding is performed by a sum-product algorithm. The performance of the proposed scheme can achieve a reasonable DC-suppression and a low bit error rate.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.486-489
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• 2010

This paper describes a layered LDPC decoder which supports block length of 1,944 bits and code rate 1/2 for IEEE 802.11n WLAN standard. To reduce the hardware complexity, the min-sum algorithm and layered architecture is adopted. A novel memory reduction technique suitable for min-sum algorithm reduces memory size by 75% compared with conventional method. The designed processor has 200,400 gates and 19,400 bits memory, and it is verified by FPGA implementation. The estimated throughput is about 200 Mbps at 120 MHz clock by using Xilinx Virtex-4 FPGA device.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.1
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• pp.53-57
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• 2010

Low-density parity-check (LDPC) codes with belief-propagation (BP) algorithm achieve a remarkable performance close to the Shannon limit at reasonable decoding complexity. Conventionally, each iteration in decoding process contains two steps, the horizontal step and the vertical step. In this paper, an efficient implementation of the adaptive offset min-sum (AOMS) algorithm for decoding LDPC codes using the single-step method is proposed. Furthermore, the performances of the AOMS algorithm compared with belief-propagation (BP) algorithm are investigated. The algorithms using the single-step method reduce the implementation complexity, speed up the decoding process and have better efficiency in terms of memory requirements.