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Computer Engineering and Applications Journal

Parallel complementary decoding based on OSD and Chase

Zijian Dong

Published Jan 1, 2009• 0 citations
OpenAlex

Abstract

Ordered Statistic Decoding(OSD) algorithm and Chase algorithm are investigated in this paper,based on which,a new Chase-OSD parallel decoding algorithm for medium and short lengths Low Density Parity-Check(LDPC) codes is proposed.Chasetype decoding algorithm is based on processing certain LRPs of a received sequence,while OSD algorithm is based on processing certain MRIPs of a received sequence.If there are too many errors in MRIPs,the OSD algorithm will fail,while there are too much errors in LRPs,the Chase-type algorithm will fail.A parallel concatenation decoding algorithm is proposed based on that complementary characteristic.The simulation results show that the proposed algorithm is effective.The decoding performance is improved compared with BP-OSD and BP-Chase algorithm.

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Ordered Statistic Decoding(OSD) algorithm and Chase algorithm are investigated in this paper,based on which,a new Chase-OSD parallel decoding algorithm for medium and short lengths Low Density Parity-Check(LDPC) codes is proposed.Chasetype decoding algorithm is based on processing certain LRPs of a received sequence,while OSD algorithm is based on processing certain MRIPs of a received sequence.If there are too many errors in MRIPs,the OSD algorithm will fail,while there are too much errors in LRPs,the Chase-type algorithm will fail.A parallel concatenation decoding algorithm is proposed based on that complementary characteristic.The simulation results show that the proposed algorithm is effective.The decoding performance is improved compared with BP-OSD and BP-Chase algorithm.
In this contribution, KNIH algorithm and Ordered Statistic Decoding (OSD) algorithm are investigated, based on which, a novel KNIH-OSD parallel decoding scheme for LDPC codes is proposed. KNIH decoding algorithm processes certain LRPs of a received sequence, while OSD algorithm processes certain MRIPs of a received sequence. If there are too many errors in MRIPs, the OSD algorithm will fail, on the contrary, if there are too many errors in LRPs, the KNIH algorithm will fail. This contribution proposes a parallel decoding scheme based on the complementary characteristic of these two algorithms. Simulation results show that the proposed scheme is feasible and effective. Compared with OSD and KNIH algorithm, the decoding performance is improved.
According to the error-correcting capability complementarity of Chase decoding algorithm and Ordered Statistic Decoding(OSD) algorithm,a new Chase-OSD parallel decoding algorithm for RM codes is proposed,in which,OSD algorithm processes certain MRIPs of a received sequence,while Chase-type decoding algorithm processes certain LRPs of a received sequence.If there are at least i+1 MRIPs of the ordered received sequence in error,OSD algorithm will fail.On the other hand,if the number of errors in the LRPs is large,the Chase-type algorithm will fail.A parallel decoding algorithm based on complementary characteristic is proposed.Simulation experimental results show this algorithm can achieve better decoding performance.
This paper analyses the ordered statistic decoding(OSD) algorithm of short LDPC codes and investigates BP-OSD concatenation algorithm and LLR accumulation algorithm.Considering the tradeoff between the complexity and performance of decoding,the min-sum algorithm was used instead of the BP algorithm,and it was concatenated with LLR accumulation algorithm.Simulation results show that compared with the original BP algorithm,the performance of the improved concatenation algorithm has been greatly raised,and compared with the BP-OSD concatenation algorithm,its decoding complexity has been reduced and the performance is nearly the same.
In this paper, we propose an efficient decoding algorithm for short low-density parity check (LDPC) codes by carefully combining the belief propagation (BP) decoding and ordered statistics decoding (OSD) algorithms. Specifically, a modified BP (mBP) algorithm is applied for a certain number of iterations prior to OSD to enhance the reliability of the received message, where an offset parameter is utilized in mBP to control the weight of the extrinsic information in message passing. By carefully selecting the offset parameter and the number of mBP iterations, the number of errors in the most reliable positions (MRPs) in OSD can be reduced by mBP, thereby significantly improving the overall decoding performance of error rate and complexity. Simulation results show that the proposed algorithm can approach the maximum-likelihood decoding (MLD) for short LDPC codes with only a slight increase in complexity compared to BP and a significant decrease compared to OSD. Specifically, the order- (m -1) decoding of the proposed algorithm can achieve the performance of the order-m OSD.
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In this work, we use restricted likelihood information of belief propagation (BP) algorithm to improve the accuracy of sorting in order statistic decoding (OSD) for low-density parity-check (LDPC) codes. The reliability information delivered from the last BP iteration to OSD algorithm is inaccurate because that the propagation information may be enlarged for the existence of girths, thence limitation on iterative information can been applied to improve the OSD decoding performance. Simulation results show that the proposed method is effective.