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Conference on Communication Networks and Services Research

MP&A Mixed Decoding Algorithm for LDPC Codes

Chia‐Lu Ho, Hsu-Hung Yang

Published May 1, 2007• 0 citations
Publisher

Abstract

Because the message passing (MP) method is suboptimum and optimum solutions are not guaranteed, we present a hybrid decoding method by combing the MP and the A* methods. We first make comparison between the MP and A* method and then show their combined performance. Using the hybrid structure, its decoding gain is the same as that of A* method. Moreover, decoding complexity is slightly greater than that of MP one. For codeword length 96 bits and coding rate 1/2 and BER = 10-5, the hybrid structure outperforms 1.4 dB decoding gain than the MP method. This improvement only required 1% received sequences to be transferred to A* decoding block. Our newly designed hybrid structure can solve both of the high decoding gain and low decoding complexity while it has the ability to yield the optimum solution.

DOI
10.1109/cnsr.2007.43

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Because the message passing (MP) method is suboptimum and optimum solutions are not guaranteed, we present a hybrid decoding method by combing the MP and the A* methods. We first make comparison between the MP and A* method and then show their combined performance. Using the hybrid structure, its decoding gain is the same as that of A* method. Moreover, decoding complexity is slightly greater than that of MP one. For codeword length 96 bits and coding rate 1/2 and BER = 10-5, the hybrid structure outperforms 1.4 dB decoding gain than the MP method. This improvement only required 1% received sequences to be transferred to A* decoding block. Our newly designed hybrid structure can solve both of the high decoding gain and low decoding complexity while it has the ability to yield the optimum solution.
LDPC code used by the advanced communication standard of the next generation is an error control code. Its error correction ability may approach the Shannon’s theoretical value. With the MP algorithm, it can decode received samples in high speed from transmitter. However, the MP method is suboptimum and optimum solution is not guaranteed. In this thesis, a hybrid decoding method is formed by combing the MP and the A* methods. We first make comparison between the MP and A* method and then show their combined performance. From the results, the coding gain of A* model is higher than that of MP model. The decoding complexity increases exponentially with the codeword length for A* method, but the MP method assumes linear increase. Using the hybrid structure, its coding gain is the same as that of A* method. Moreover, decoding complexity is slightly greater than that of MP one. For codeword length 96 bits and coding rate 1/2 and BER = 10E-5, the hybrid structure outperforms 1.4 dB coding gain than the MP method. This improvement only required 1% received sequences to be sent to A* decoding block. Our newly designed hybrid structure can solve both of the high coding gain and low decoding complexity while it has the ability to yield the optimum solution.
The popular LDPC decoding algorithms based on the message passing (MP) algorithm have high decoding performances. However, they are noticeably inferior to the maximum likelihood (ML) decoding algorithm. This work proposes a genetics-aided message passing (GA-MP) algorithm by applying a new genetic algorithm to MP algorithm. As a result, significantly performance improvement over MP algorithm can be achieved. Besides, compared with other genetic-aided decoding algorithms, the proposed algorithm has much better performances and much lower computational complexity. Simulations show that the decoding performance of GA-MP algorithm can achieve performances very close to the algorithm, while outperform MP algorithm. Besides, its performance will grow proportionally with the generation number without leveling off as observed in conventional MP algorithms, under high SNR condition.
Recently, non-binary low-density parity-check (NB-LDPC) codes starts to show their superiority in achieving significant coding gains when moderate codeword lengths are adopted. However, the overwhelming decoding complexity keeps NB-LDPC codes from being widely employed in modern communication devices. This paper proposes a hybrid message-passing decoding algorithm which consumes very low computational complexity. It achieves competitive error performance compared with conventional Min-max algorithm. Simulation result on a (255,174) cyclic code shows that this algorithm obtains at least 0.5dB coding gain over other state-of-the-art low-complexity NB-LDPC decoding algorithms. A partial-parallel NB-LDPC decoder architecture for cyclic NB-LDPC codes is also developed based on this algorithm. Optimization schemes are employed to cut off hard decision symbols in RAMs and also to store only part of the reliability messages. In addition, the variable node units are redesigned especially for the proposed algorithm. Synthesis results demonstrate that about 24.3% gates and 12% memories can be saved over previous works.
Introduced is a new type of message-passing (MP) decoders for low-density parity-check (LDPC) codes over the binary symmetric channel. Unlike traditional belief propagation (BP) based MP algorithms which propagate probabilities or log-likelihoods, the new MP decoders propagate messages requiring only a finite number of bits for their representation in such a way that good performance in the error floor region is ensured. Additionally, these messages are not quantised probabilities or log-likelihoods. As examples, MP decoders are provided that require only three bits for message representation, but surpass the floating-point BP (which requires a large number of bits for representation) in the error-floor region.
In this paper, an iterative soft-decision hybrid decoding algorithm for non-binary low-density parity-check (LDPC) codes with short codeword lengths is proposed. The rationale of the approach is to combine the classical belief propagation (BP) iterative LDPC decoding algorithm with the most reliable basis (MRB) decoding algorithm. This allows to achieve significant performance improvements, with a complexity that, for medium/low error rates, is only slightly higher than that of the BP algorithm alone. The performance improvement with respect to pure BP decoding is up to 0.7 dB at codeword error rate (CER) ≈ 10-5. Notably, for a fixed MRB order, hybrid decoding achieves a gain up to 0.5 dB at CER ≈ 10-5with respect to BP decoding and MRB decoding used alone.
LDPC convolutional codes (LDPC-CC) are a family of error-correcting codes (ECC) used in digital communication systems like the IEEE 1901 standard. High throughput and low complexity hardware architectures were designed for real time systems. In this article we demonstrate that an efficient selection of the message passing (MP) algorithm for LDPC-CC decoding improves the architecture features of related works. In fact, considering the LDPC-CC decoders proposed for the IEEE 1901 standard, we show that an appropriate Min-Sum approximation selection can significantly improve the error correction performance by 0.1 to 0.2 dB in terms of Bit Error Ratio. It can also reduce the hardware complexity by 10% to 20% with no impact on the Bit Error Ratio performance.