一种改进的LDPC码硬判决译码算法

LDPC码的硬判决译码通常是利用比特翻转算法(BF)以及在其基础上改进的加权比特翻转算法(WBF)来实现的,但是前者算法性能较差,而后者的复杂度较高,为了让译码算法能够兼顾其性能和复杂度,针对之前的BF以及WBF算法,提出了一种改进的LDPC码硬判决译码算法,该算法能够在前两次迭代中完成多个比特位的翻转.仿真结果表明,这种改进的算法可以在性能损失较小的条件下,大大降低算法的复杂度,从而提高译码的效率,减轻硬件的负担.     

LDPC码加权比特翻转译码算法的低复杂度提前停止准则

近年来,针对LDPC码置信传播(BP)译码算法的提前停止准则的研究已经有了很多,但设计适合加权比特翻转(WBF)译码算法的提前停止准则却研究甚少。依据对WBF算法的全新理解方式,该文提出一种实现简单、适用性强的WBF算法提前停止准则,它能在译码的初始阶段检测绝大多数不可纠错的帧。仿真结果表明,基于提前停止准则的WBF算法在性能损失可以忽略的条件下,极大地降低迭代次数,在实现复杂度和性能之间达到了很好的折中。     

一种简化的LDPC码BP译码算法的研究

低密度奇偶校验码(LDPC码)是一种逼近香农限的线性分组码,译码的复杂度较低;在LDPC码译码算法中性能较好的是置信传播译码(BP)算法,他能够在迭代译码过程中确定码字是否已译出,但是复杂度高,运算量大。采用一种改进的BP译码算法,在迭代译码过程中对校验节点的更新信息进行曲线拟合,以减小译码运算量,有利于硬件的并行实现,减少译码延时。仿真结果表明,改进的BP算法译码性能和原来的BP算法接近,而且复杂度较低。     

LDPC码的一种高效加权比特翻转译码算法

针对低密度奇偶校验(LDPC)码中加权比特翻转(WBF)译码算法在迭代过程中绝大多数情况都是进行单比特翻转,导致译码效率低并且可能会发生比特翻转"死循环"的现象,提出一种更为高效的加权比特翻转(EWBF)算法.该算法对翻转阈值进行了改进,使得每次迭代能够翻转多个比特,提高译码效率,并且能够避免译码过程出现的翻转"死循环"现象.仿真结果表明,所提译码算法与WBF算法、改进的WBF(MWBF)算法和IMWBF(Improved MWBF)算法相比,平均迭代次数分别降低51.6%~56.2%、49.6%~54.2%和48.1%~51.3%;而在译码性能方面,算法性能接近甚至优于IMWBF算法,当最大迭代次数设定为30次时,相比于IMWBF算法,在误码率为10-4时可获得0.92 dB的增益.     

LDPC短码WBF-OSD组合译码设计

为了在译码性能和复杂度之间取得折中,针对低密度奇偶校验（Low Density Parity Check,LDPC）短码设计了加权比特翻转（Weighted Bit-Flipping,WBF）译码与顺序统计量译码（Ordered Statistics Decoding,OSD）的组合译码方法。在接收端,首先进行WBF译码,如果译码失败,则将原始接收序列送入OSD进行译码,最后输出OSD译码结果,这种组合方式称为WBF-OSD-I译码。为了进一步提高译码性能,考虑到WBF-OSD-I译码算法中WBF译码存在的不可检错误导致译码错误的接收序列并没有进入OSD译码器进行译码,设计了WBF-OSD-II组合译码方式。这种WBF-OSD-II组合译码方式通过比较WBF译出的估计码字与接收序列的距离,根据选择的门限决定是否使用OSD译码,从而进一步降低译码错误概率。仿真分析验证了LDPC短码的WBF-OSD组合译码性能。     

基于多/单比特切换机制的LDPC码两级WBF算法

为了提高低密度奇偶校验(LDPC)码的加权比特翻转(WBF)译码算法的译码速度和性能,文章提出了一种具有多/单比特切换机制的两级WBF译码算法.译码首先在第一级解码器中进行多比特翻转译码,当发现循环翻转或最大翻转函数值小于零时,跳到第二级解码器中进行单比特翻转继续译码,从而消除多比特的循环翻转和实现多比特向单比特译码的...     

IRA码最小和译码算法的改进算法

研究了重复累积(IRA)码的简化译码算法.IRA码的BP译码算法具有较高的复杂度,为了降低复杂度,首先提出将最小和算法应用于IRA码.然而,最小和算法使译码性能降低约1.2 dB.为了在复杂度和译码复杂度之间取得较好的折衷,提出了对IRA码的最小和算法的改进算法:归一化算法和偏移算法.仿真结果表明,IRA码归一化算法和偏移算法在复杂度略有增加的情况下,性能得到明显改善.     

LDPC码的改进迭代比特翻转译码算法

为提高低密度奇偶校验(LDPC)码的低复杂度硬判决译码算法的性能,提出了一种改进的比特翻转(BF)译码算法,在迭代时利用一个交替的门限模式对多个比特进行翻转,降低了每次迭代时比特被错误翻转的概率,从而有效提高了译码性能.仿真结果表明,与BF算法相比,该算法在保持低复杂度的基础上获得了更好的译码性能和更快的收敛速度.     

一种改进的RA译码算法

重复累积(RA)码译码使用置信传播(BP)算法,具有接近香农限的性能,但校验节点更新时使用复杂的双曲正切函数和反双曲正切函数,算法复杂度较高。为了降低译码算法的复杂度,且具有较好的性能,该文将查表法和分段函数近似法结合起来,提出了一种改进的译码算法。该算法采用分段的一次函数,去近似BP算法检验节点变换化简后的原函数,采用非常小的查找表得到一个校正值,用校正值去修正近似函数和变换化简后的原函数之间的误差,很好地避免了复杂函数的计算,且误差极小。该算法大大降低了译码算法的复杂度,且具有接近BP算法的译码性能。     

LDPC码加权比特翻转译码算法研究

近年来,基于置信传播(BP),最小和(MS)和归一化最小和(NMS)算法,已经提出3种相对应的LDPC码加权比特翻转(WBF)译码算法。但这3种WBF算法所代表的物理意义和内在的紧密联系问题目前仍未有所研究。该文依据一种全新的理解方式,对3种WBF算法进行理论推导,并阐述3种算法内在的紧密联系,最后通过仿真验证所得结论的合理性和正确性。这对于设计新的改进型WBF算法具有一定的指导意义。     

Hybrid Iterative Decoding for Low-Density Parity-Check Codes Based on Finite Geometries

In this letter, a two-stage hybrid iterative decoding algorithm which combines two iterative decoding algorithms is proposed to reduce the computational complexity of finite geometry low-density parity-check (FG-LDPC) codes. We introduce a fast weighted bit-flipping (WBF) decoding algorithm for the first stage decoding. If the first stage decoding fails, the decoding is continued by the powerful belief propagation (BP) algorithm. The proposed hybrid decoding algorithm greatly reduces the computational complexity while maintains the same performance compared to that of using the BP algorithm only.     

New insights into weighted bit-flipping decoding

A natural relationship between weighted bit-flipping (WBF) decoding and belief-propagation-like (BP-like) decoding is explored. This understanding can help us develop WBF algorithms from BP-like algorithms. For min-sum decoding, one can find that its WBF algorithm is the algorithm proposed by Jiang et al. For BP decoding, we propose a new WBF algorithm and show its performance advantage. The proposed WBF algorithms are parallelized to achieve rapid convergence. Two efficient simulation-based procedures are proposed for the optimization of the associated thresholds.     

Iterative decoding of one-step majority logic deductible codesbased on belief propagation

Previously, the belief propagation (BP) algorithm has received a lot of attention in the coding community, mostly due to its near-optimum decoding for low-density parity check (LDPC) codes and its connection to turbo decoding. In this paper, we investigate the performance achieved by the BP algorithm for decoding one-step majority logic decodable (OSMLD) codes. The BP algorithm is expressed in terms of likelihood ratios rather than probabilities, as conventionally presented. The proposed algorithm fits better the decoding of OSMLD codes with respect to its numerical stability due to the fact that the weights of their check sums are often much higher than that of the corresponding LDPC codes. Although it has been believed that OSMLD codes are far inferior to LDPC codes, we show that for medium code lengths (say between 200-1000 bits), the BP decoding of OSMLD codes can significantly outperform BP decoding of their equivalent LDPC codes. The reasons for this behavior are elaborated     

A high‐performance belief propagation decoding algorithm for codes with short cycles

The simplicity of decoding is one of the most important characteristics of the low density parity check (LDPC) codes. Belief propagation (BP) decoding algorithm is a well‐known decoding algorithm for LDPC codes. Most LDPC codes with long lengths have short cycles in their Tanner graphs, which reduce the performance of the BP algorithm. In this paper, we present 2 methods to improve the BP decoding algorithm for LDPC codes. In these methods, the calculation of the variable nodes is controlled by using “multiplicative correction factor” and “additive correction factor.” These factors are obtained for 2 separate channels, namely additive white Gaussian noise (AWGN) and binary symmetric channel (BSC), as 2 functions of code and channel parameters. Moreover, we use the BP‐based method in the calculation of the check nodes, which reduces the required resources. Simulation results show the proposed algorithm has better performance and lower decoding error as compared to BP and similar methods like normalized‐BP and offset‐BP algorithms.     

Belief propagation decoding of Reed-Solomon codes; a bit-level soft decision decoding algorithm

In this article we propose the application of Belief Propagation (BP) algorithm as a novel bit-level soft decision decoding (SDD) technique for Reed-Solomon (RS) codes. A brief tutorial on Belief Propagation algorithm is presented. A central issue in the application of BP algorithm to decoding RS codes is the construction of a sparse parity check matrix for the binary image of the code. It is demonstrated that Vardy's technique may be applied to find a sparse parity check matrix for RS codes. However, this technique is not applicable to all cases. The BP algorithm is applied to two test codes. In one case, simulation models show that the BP algorithm outperforms the hard decision Euclidean decoding by more than 2 dB of additional coding gain. The results with the second test code are not as promising.     

Low-Density Parity-Check Codes with 2-State Trellis Decoding

A class of low-density parity-check (LDPC) codes with a simple 2-state trellis structure is presented. For LDPC decoding, the conventional belief propagation (BP) algorithm consists of numerous sub-decoders of single-parity check codes and exchanges information between sub-decoders in an iterative manner. If the single-parity check codes can be constructed and grouped in a proper way, the decoder can be decomposed into few identical 2-state trellis decoders. Therefore, instead of numerous sub-decoders of single-parity check codes, an iterative decoding algorithm based on few sub-decoders over 2-state trellis is proposed. The proposed decoding algorithm improves the efficiency of message passing between sub-decoders and hence provides a fast convergent rate as compared to the standard BP algorithm. Simulation results show that the proposed scheme provides a better performance and a fast convergent rate as compared to those of standard BP algorithm. The result also shows that the proposed algorithm has a similar performance as that of asynchronous replica shuffled BP algorithm and has a slightly inferior performance than that of synchronous replica shuffled BP algorithm. However, complexity analysis shows that our proposed algorithm has complexity that is lower than that of the replica shuffled BP algorithm.     

一种低迭代次数的极化码置信传播译码算法

针对置信传播(Belief Propagation,BP)译码算法在迭代次数较多时吞吐量和译码时延性能提升受限的问题,提出了一种低迭代次数的极化码BP译码算法,通过采用比特翻转和子信道冻结的方式,降低译码过程中的迭代次数.仿真结果表明,相对于传统极化码BP译码算法(设置最大迭代次数为40次),所提算法在信噪比为3 dB...