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Generic model of LDPC code decoders

Emmanuel Boutillon

Published Oct 6, 2006• 0 citations
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Elsevier eBooks•Dec 12, 2017•0 citations
In this paper, we propose an extended layered decoding approach for low density parity check (LDPC) codes. Compared to conventional layered decoding algorithms, the proposed approach has no constraint in the column weight of each layer. Hence, it enables more flexibility in high-throughput LDPC decoder design with layered decoding. Simulations on structured and random LDPC codes show that the proposed decoding method achieves significantly faster convergence and slightly better error correction performance than the conventional two phase massage passing sum-product algorithm. We also propose an efficient highly parallel decoder architecture for generic quasi-cyclic LDPC codes to facilitate the practical application of the proposed decoding scheme.
The Low-Density Parity-Check codes are among the most powerful forward error correcting codes, since they enable to get as close as a fraction of a dB from the Shannon limit.This astonishing performance combined with their relatively simple decoding algorithmmake these codes very attractive for the next digital transmission system generations. Itis already the case for the next digital satellite broadcasting standard (DVB-S2), where an irregular LDPC code has been chosen to protect the downlink information. In this thesis, we focused our research on the iterative decoding algorithms and their hardware implementations. We proposed first a suboptimal algorithm named the λ-min algorithm. It reduces significantly the complexity of the decoder without any significant performance loss, as compared to the belief propagation (BP) algorithm. Then we studied and designed a generic architecture of an LDPC decoder, which has been implemented on a FPGA based platform. This hardware decoder enables to accelerate the simulations more than 500 times as compared to software simulations. Moreover, based on an all-tunable design, our decoder features many facilities: It is possible to configure it for a very wide code family, so that the research for good codes is processed faster ; thanks to the genericity of the processing components, it is also possible to optimize the internal coding format, and even to compare various decoding algorithms and various processing schedules. Finally, our experience in the area of LDPC decoders led us to propose a formal framework for analysing the architectures of LDPC decoders. This framework encompassesboth the datapath (parallelism, node processors architectures) and the control mode associated to the several decoding schedules. Thus within this framework, a classification of the different state-of-the-art LDPC decoders is proposed. Moreover, some synthesis of efficient and unpublished architectures have been also proposed.