Two-Bit Bit Flipping Decoding of LDPC Codes

In this paper, we propose a new class of bit flipping algorithms for low-density parity-check (LDPC) codes over the binary symmetric channel (BSC). Compared to the regular (parallel or serial) bit flipping algorithms, the proposed algorithms employ one additional bit at a variable node to represent its "strength." The introduction of this additional bit increases the guaranteed error correction capability by a factor of at least 2. An additional bit can also be employed at a check node to capture information which is beneficial to decoding. A framework for failure analysis of the proposed algorithms is described. These algorithms outperform the Gallager A/B algorithm and the min-sum algorithm at much lower complexity. Concatenation of two-bit bit flipping algorithms show a potential to approach the performance of belief propagation (BP) decoding in the error floor region, also at lower complexity.Comment: 6 pages. Submitted to IEEE International Symposium on Information Theory 201

Reliability Ratio Based Weighted Bit-Flipping Decoding for LDPC Codes

In this contribution, a novel reliability-ratio based weighted bit-flipping(RRWBF) algorithm is proposed for decoding Low Density Parity Check (LDPC) codes. The RRWBF algorithm proposed is benchmarked against the conventional weighted bit-flipping (WBF) algorithm [1] and the improved weighted bit-flipping (IWBF) algorithm [2]. More than 1 and 2 dB coding gain was achieved at an BER of 10-5 while invoking the RRWBF algorithm in comparison to the two benchmarking schemes, when communicating over an AWGN and an uncorrelated Rayleigh channel, respectively. Furthermore, the decoding complexity of the proposed RRWBF algorithm is maintained at the same level as that of the conventional WBF algorithm

New low-density-parity-check decoding approach based on the hard and soft decisions algorithms

It is proved that hard decision algorithms are more appropriate than a soft decision for low-density parity-check (LDPC) decoding since they are less complex at the decoding level. On the other hand, it is notable that the soft decision algorithm outperforms the hard decision one in terms of the bit error rate (BER) gap. In order to minimize the BER and the gap between these two families of LDPC codes, a new LDPC decoding algorithm is suggested in this paper, which is based on both the normalized min-sum (NMS) and modified-weighted bit-flipping (MWBF). The proposed algorithm is named normalized min sum- modified weighted bit flipping (NMSMWBF). The MWBF is executed after the NMS algorithm. The simulations show that our algorithm outperforms the NMS in terms of BER at 10-8 over the additive white gaussian noise (AWGN) channel by 0.25 dB. Furthermore, the proposed NMSMWBF and the NMS are both at the same level of decoding difficulty

LDPC codes

Práce se zabývá problematikou LDPC kódů. Jsou zde popsány metody vytváření paritní matice, kde je kladen důraz především na strukturované vytváření této matice za použití konečné geometrie: Euklidovské geometrie a projektivní geometrie. Další oblastí, které se práce věnuje je dekódování LDPC kódů. Práce porovnává čtyři dekódovací metody: Hard-Decision algoritmus, Bit-Flipping algoritmus, The Sum-Product algoritmus a Log Likelihood algoritmus, při kterých je kladen důraz především na iterativní dekódovací metody. Praktickým výstupem práce je program LDPC kódy, který vznik v prostředí Matlab. Tento program je rozdělen na dvě části -- Výuka LDPC kódů a Simulace LDPC kódů. Na základě výsledků získaných z programu Simulace LDPC kódů je vytvořeno porovnání vytvářecích a dekódovacích metod LDPC kódů. Pro porovnávání dekódovacích metod LDPC kódů byly využity BER charakteristiky a časová závislost jednotlivých metod na různých parametrech LDPC kódu (počet iterací nebo velikost paritní matice).The aim of this thesis are problematics about LDPC codes. There are described metods to create parity check matrix, where are important structured metods using finite geometry: Euclidean geometry and projectice geometry. Next area in this thesis is decoding LDPC codes. There are presented four metods: Hard-Decision algorithm, Bit-Flipping algorithm, The Sum-Product algorithm and Log Likelihood algorithm, where is mainly focused on iterative decoding methods. Practical output of this work is program LDPC codes created in environment Matlab. The program is divided to two parts -- Practise LDPC codes and Simulation LDPC codes. The result reached by program Simulation LDPC codes is used to create a comparison of creating and decoding methods LDPC codes. For comparison of decoding methods LDPC codes were used BER characteristics and time dependence each method on various parameters LDPC code (number of iteration or size of parity matrix).

The decoding failure probability of MDPC codes

Moderate Density Parity Check (MDPC) codes are defined here as codes which have a parity-check matrix whose row weight is $O(\sqrt{n})$ where $n$ is the length $n$ of the code. They can be decoded like LDPC codes but they decode much less errors than LDPC codes: the number of errors they can decode in this case is of order $\Theta(\sqrt{n})$. Despite this fact they have been proved very useful in cryptography for devising key exchange mechanisms. They have also been proposed in McEliece type cryptosystems. However in this case, the parameters that have been proposed in \cite{MTSB13} were broken in \cite{GJS16}. This attack exploits the fact that the decoding failure probability is non-negligible. We show here that this attack can be thwarted by choosing the parameters in a more conservative way. We first show that such codes can decode with a simple bit-flipping decoder any pattern of $O\left(\frac{\sqrt{n} \log \log n}{\log n}\right)$ errors. This avoids the previous attack at the cost of significantly increasing the key size of the scheme. We then show that under a very reasonable assumption the decoding failure probability decays almost exponentially with the codelength with just two iterations of bit-flipping. With an additional assumption it has even been proved that it decays exponentially with an unbounded number of iterations and we show that in this case the increase of the key size which is required for resisting to the attack of \cite{GJS16} is only moderate

Linear-time encoding and decoding of low-density parity-check codes

Low-density parity-check (LDPC) codes had a renaissance when they were rediscovered in the 1990’s. Since then LDPC codes have been an important part of the field of error-correcting codes, and have been shown to be able to approach the Shannon capacity, the limit at which we can reliably transmit information over noisy channels. Following this, many modern communications standards have adopted LDPC codes. Error-correction is equally important in protecting data from corruption on a hard-drive as it is in deep-space communications. It is most commonly used for example for reliable wireless transmission of data to mobile devices. For practical purposes, both encoding and decoding need to be of low complexity to achieve high throughput and low power consumption. This thesis provides a literature review of the current state-of-the-art in encoding and decoding of LDPC codes. Message- passing decoders are still capable of achieving the best error-correcting performance, while more recently considered bit-flipping decoders are providing a low-complexity alternative, albeit with some loss in error-correcting performance. An implementation of a low-complexity stochastic bit-flipping decoder is also presented. It is implemented for Graphics Processing Units (GPUs) in a parallel fashion, providing a peak throughput of 1.2 Gb/s, which is significantly higher than previous decoder implementations on GPUs. The error-correcting performance of a range of decoders has also been tested, showing that the stochastic bit-flipping decoder provides relatively good error-correcting performance with low complexity. Finally, a brief comparison of encoding complexities for two code ensembles is also presented

Network coding schemes with efficient LDPC coded MIMO–NOMA in two-way relay networks

The combination of non-orthogonal multiple access (NOMA) and multi-input multi-output (MIMO) approaches has been considered as assuring multiple access for the fifth generation technology. In this study, the performance of a 2 × 2 MIMO- NOMA system with low-density parity check (LDPC) codes is investigated. Redundancy with randomly interleaved differential encoding (R-RIDE) is proposed and applied to LDPC encoded messages by two users. LDPC decoding is done using the sum-product algorithm (SPA), which has two types of decoding methods, hard-decision and soft-decision. For hard-decision, bit-flipping decoder is used and for soft-decision, probability domain, log-domain, and simplified log-domain decoders are used. Bit error rate (BER) versus signal-to-noise ratio (SNR) in (dB) and average mutual information (AMI) in (bps/Hz) versus SNR (dB) are evaluated to compare the performance of the proposed and conventional LDPC schemes in NOMA and MIMO-NOMA systems. Simulation results show that both AMI and BER of the proposed LDPC-R-RIDE in MIMO-NOMA system greatly outperforms conventional LDPC coded schemes in NOMA and MIMO-NOMA systems. Moreover, the proposed R-RIDE-LDPC in MIMO-NOMA system outperforms the proposed scheme in the NOMA system. From the simulation results, LDPC-R-RIDE with simplified log-domain decoder has the best AMI result and BER performance compared with other decoding methods