Improved Gradient Descent Bit Flipping algorithms for LDPC decoding

Phromsa-ard, Tharathorn; Arpornsiripat, Jiratchaporn; Wetcharungsri, Jutaphet; Sangwongngam, Paramin; Sripimanwat, Keattisak; Vanichchanunt, Pisit

doi:10.1109/dictap.2012.6215420

Cited by 8 publications

(9 citation statements)

References 13 publications

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“…We also introduce a new method called Smoothed M-NGDBF (SM-NGDBF) that contributes an additional 0.3 dB gain at the cost of additional iterations. It should be noted that Wadayama et al proposed using a small random perturbation in the H-GDBF thresholds [9]; the NGDBF methods use a larger [24] Good Serial Moderate IMWBF [25] Excellent Serial High PWBF [7] Excellent Parallel High S-GDBF [9] Fair Serial Low M-GDBF [9] Good Mixed Low H-GDBF [9] Excellent Mixed High AT-GDBF [10] Good Parallel Low IGDBF [12] Excellent Mixed Moderate RRWGDBF [11] Excellent Parallel High perturbation in combination with other heuristics to obtain good performance with very low complexity.…”

Section: Related Workmentioning

confidence: 99%

Noisy Gradient Descent Bit-Flip Decoding for LDPC Codes

Sundararajan

Winstead

Boutillon

2014

IEEE Trans. Commun.

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A modified Gradient Descent Bit Flipping (GDBF) algorithm is proposed for decoding Low Density Parity Check (LDPC) codes on the binary-input additive white Gaussian noise channel. The new algorithm, called Noisy GDBF (NGDBF), introduces a random perturbation into each symbol metric at each iteration. The noise perturbation allows the algorithm to escape from undesirable local maxima, resulting in improved performance. A combination of heuristic improvements to the algorithm are proposed and evaluated. When the proposed heuristics are applied, NGDBF performs better than any previously reported GDBF variant, and comes within 0.5 dB of the belief propagation algorithm for several tested codes. Unlike other previous GDBF algorithms that provide an escape from local maxima, the proposed algorithm uses only local, fully parallelizable operations and does not require computing a global objective function or a sort over symbol metrics, making it highly efficient in comparison. The proposed NGDBF algorithm requires channel state information which must be obtained from a signal to noise ratio (SNR) estimator. Architectural details are presented for implementing the NGDBF algorithm. Complexity analysis and optimizations are also discussed.Comment: 16 pages, 22 figures, 2 table

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Section: Related Workmentioning

confidence: 99%

Noisy Gradient Descent Bit-Flip Decoding for LDPC Codes

Sundararajan

Winstead

Boutillon

2014

IEEE Trans. Commun.

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“…The procedure of the proposed simple decoding of bit-flipping algorithm is modified and applied [25] by the following sub step:…”

Section: Thenmentioning

confidence: 99%

Low-complexity key reconciliation algorithm using LDPC bit-flipping decoding for quantum key distribution

Phromsa-ard

Sangwongngam

Sripimanwat

et al. 2014

2014 11th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technolo

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Quantum key reconciliation is an essential process of quantum key distribution (QKD). It aims to correct the transmission errors after the distribution of quantum objects over a quantum channel, where two legitimate parties use a classical public authenticated channel to disclose correlated bits for agreeing on their common key. This work proposes an alternative promising method employing LDPC-codes bitflipping decoding to practical implementation of quantum key reconciliation. In our proposed scheme, the low-complexity code bit-flipping decoding based on syndrome decoding is modified and applied to conventional Winnow protocol to achieve both error correcting performance and low complexity of hardware realization, i.e. FPGA logic cells and/or memory. From numerical simulation while the performance of our proposed scheme in terms of final bit error rate (BER) and disclosed bits is superior to conventional Winnow and CASCADE protocols, it yields low complexity in LDPC decoding comparable to the existing LDPCbased reconciliation protocols. Therefore, the technique is promising to high-speed discrete-variable QKD applications.

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“…To overcome these problems, the hard-decision algorithms have been largely investigated and numerous variants of BF algorithms has been proposed. Among which the weighted BF (WBF) algorithm [12], the modified weighted BF (MWBF) algorithm [13], gradient descent bit-flipping GDBF [11] and reliability ratio weighted GDBF (RRWGDBF) [14]. These works use an additive or multiplicative weighting factors in Δk(x) to evaluate the reliability of syndromes [15], [16].…”

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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Improved Gradient Descent Bit Flipping algorithms for LDPC decoding

Cited by 8 publications

References 13 publications

Noisy Gradient Descent Bit-Flip Decoding for LDPC Codes

Noisy Gradient Descent Bit-Flip Decoding for LDPC Codes

Low-complexity key reconciliation algorithm using LDPC bit-flipping decoding for quantum key distribution

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

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