Fast DSP Implementation of a Low Complexity LDPC Decoder

Razi, Mouhcine; Mansouri, Anas; Benhayoun, Mhammed; Madi, Abdessalam Aït; Ahaitouf, Ali

doi:10.1109/wits.2019.8723838

Cited by 3 publications

(1 citation statement)

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“…The soft-decision algorithms calculate the extrinsic log likelihood ratio (LLRs) to evaluate the reliability of received messages ( n), these methods achieve the best bit error rate (BER) performances [7]- [9], but these iterative decoding algorithms require large number of arithmetic operations; and can introduce prohibitive delays for very high-speed transmissions where latency plays an important role. Alternatively, for harddecision algorithms (or bit flipping algorithms) the decoding time can be strongly reduced with some relative loss in performances [10].…”

Section: Introductionmentioning

confidence: 99%

An improvement and a fast DSP implementation of the bit flipping algorithms for low density parity check decoder

Razi

Benhayoun

Mansouri

et al. 2021

IJECE

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<span lang="EN-US">For low density parity check (LDPC) decoding, hard-decision algorithms are sometimes more suitable than the soft-decision ones. Particularly in the high throughput and high speed applications. However, there exists a considerable gap in performances between these two classes of algorithms in favor of soft-decision algorithms. In order to reduce this gap, in this work we introduce two new improved versions of the hard-decision algorithms, the adaptative gradient descent bit-flipping (AGDBF) and adaptative reliability ratio weighted GDBF (ARRWGDBF). An adaptative weighting and correction factor is introduced in each case to improve the performances of the two algorithms allowing an important gain of bit error rate. As a second contribution of this work a real time implementation of the proposed solutions on a digital signal processors (DSP) is performed in order to optimize and improve the performance of these new approchs. The results of numerical simulations and DSP implementation reveal a faster convergence with a low processing time and a reduction in consumed memory resources when compared to soft-decision algorithms. For the irregular LDPC code, our approachs achieves gains of 0.25 and 0.15 dB respectively for the AGDBF and ARRWGDBF algorithms.</span>

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Section: Introductionmentioning

confidence: 99%