共查询到19条相似文献,搜索用时 171 毫秒
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基于串行消息传递机制的QC-LDPC码快速译码算法研究 总被引:1,自引:0,他引:1
针对准循环LDPC(QC-LDPC)码基于洪水消息传递机制译码算法的不足,该文提出了一种快速的分组串行译码算法。该算法通过将LDPC码的校验节点(或变量节点)按一定规则划分成若干个子集,在每一轮迭代过程中,依次对各个子集中的校验节点(或变量节点)并行地进行消息更新,提高了译码速度。同时根据分组规则,提出了一种有效的分组方法,并通过分析发现基于循环置换阵的准循环LDPC码非常适合采用这种分组译码算法进行译码。通过对不同消息传递机制下准循环LDPC码译码算法性能的仿真比较,验证了在复杂度不增加的情况下,该译码算法在继承了串行译码算法性能优异和迭代收敛快等优点的同时,极大地提高了准循环LDPC码的译码速度。分析表明,分组串行译码算法译码速度至少为串行译码算法的p倍(p为准循环LDPC码校验矩阵中循环置换阵的行数或列数)。 相似文献
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稀疏码多址接入(SCMA)技术作为5G无线通信网络的一个竞争性的非正交多址方案,具有广阔的应用前景.但目前基于SCMA的上行链路均采用泛洪方案的消息传递算法(MPA)进行译码,无论是检测的复杂度还是收敛速度都不甚理想.提出一种改变信息更新策略的串行消息传递算法——S-MPA (serial MPA),按照变量节点的次序进行消息处理和传递,每一个变量节点同时进行校验消息的接收和变量消息的发送.理论和仿真结果表明,该算法不仅能保持良好的性能,而且也有较低的解码复杂度. 相似文献
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为进一步改善低密度奇偶校验(LDPC)码译码算法的纠错性能,并加快其译码的收敛速度,提出一种基于交错行列消息传递的改进译码算法.该算法通过将动态调度策略译码算法中的残差值思想引入到串行调度译码算法中,使得串行调度译码算法在每次迭代进行消息更新前都会进行一次残差值排序的计算,并对其节点消息原有的固定更新顺序进行重新排序.仿真结果表明:在误码率为10-4时,该改进的译码算法相比于行消息传递算法和列消息传递算法有0.25和0.24 dB的增益;在误码率为10-5时,相比于交错行列消息传递算法有0.13 dB的增益. 相似文献
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基于联合判决消息传递机制的LDPC码译码算法研究 总被引:1,自引:0,他引:1
采用消息传递算法(Message passing algorithm)对LDPC码进行译码时,变量消息的振荡会引起错误的发生.本文以(600.300)非规则LDPC码仿真实验为例分析了不同译码效果下判决消息均值的分布特点,并结合环的特点,分析了译码产生错误判决的原因.研究了"纠删"型消息传递机制和联合判决迭代停止准则,针对判决消息出现振荡情况,提出以"纠删"方式处理变量消息的更新,并结合变量节点判决消息均值分布趋势与伴随式结果确定迭代终止条件.在此基础上,提出一种新的LDPC码译码算法.仿真分析表明,新的译码算法能够在减少迭代次数和降低译码复杂度的同时,有效提高译码的纠错性能. 相似文献
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置信传播算法(BP)是低密度校验码(LDPC)一种常用的译码算法。为了改善动态调度算法(IDS)在提高BP算法译码性能时复杂度较高的缺陷,提出了一种基于校验节点的串行消息更新策略(Min2-CSBP)。该策略定义了一种基于校验节点的可靠度测度并能近似表征对应的校验节点的可靠程度。可靠度测度仅用于确定消息更新的次序,而在消息更新的计算中仍然采用精确的概率值。每次迭代中对可靠度按升序排序并按此顺序进行消息更新。随后,对Flood算法、CSBP算法、NW-RBP算法及Min2-CSBP算法进行了复杂度对比。仿真结果表明:在使用LDPC短码时,Min2-CSBP算法比Flood算法及CSBP算法显著提高了误码率性能,并减少了迭代次数。 相似文献
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LDPC码加权位翻转解码算法的研究 总被引:1,自引:1,他引:0
本文以Tanner图上的迭代消息流传递技术为基础,分析了Gallager提出的LDPC码第一解码方案,给出基于校验和的位翻转硬判决解码算法。在此基础上引入接收信号作为可靠性评估,使评估值作为硬判决的加权系数,从而提出基于校验和的加权位翻转解码算法。加权位翻转算法充分考虑了接收符号的信息;为了快速搜索翻转位,对不满足的校验方程数采用最大投票数排队算法。这些措施的合理应用改善了基于校验和的位翻转解码算法的性能。 相似文献
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针对多元LDPC码扩展最小和(Extended Min Sum,EMS)译码算法收敛速度慢、运算复杂度高的问题,提出一种多元LDPC码列分层动态检泡(Dynamic Bubble-Check,DBC)译码算法。首先对变量节点按不同列重进行分层处理,译码时率先更新列重较大分层的变量节点消息,不同层之间采用串行方式进行消息传递,通过并串结合的方式降低译码迭代次数。在校验节点消息更新过程中,采用动态检泡方法减少EMS算法中的运算量,降低算法复杂度。仿真结果表明,在几乎不损失性能的前提下,该算法的平均最大迭代次数仅为EMS译码算法的50%,复杂度降低为EMS算法的50%。 相似文献
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改进的离散字母表迭代译码算法研究 总被引:1,自引:0,他引:1
为了优化LDPC迭代译码性能和降低算法复杂度,提出了一种改进的基于Gallager A算法的2b离散字母表迭代译码算法。在每一轮迭代中,Tanner图上的校验节点与变量节点之间所传递的消息有1b表示符号值,另1b反映码字结构特性,其中变量节点更新规则是通过查表法来实现的。在二元对称信道下针对列重为3的规则LDPC码做了仿真实验,仿真结果表明该算法性能明显优于原算法,并且具有较低的复杂度。 相似文献
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Efficient Serial Message-Passing Schedules for LDPC Decoding 总被引:1,自引:0,他引:1
Sharon E. Litsyn S. Goldberger J. 《IEEE transactions on information theory / Professional Technical Group on Information Theory》2007,53(11):4076-4091
Conventionally, in each low-density parity-check (LDPC) decoding iteration all the variable nodes and subsequently all the check nodes send messages to their neighbors (flooding schedule). An alternative, more efficient, approach is to update the nodes' messages serially (serial schedule). A theoretical analysis of serial message passing decoding schedules is presented. In particular, the evolution of the computation tree under serial scheduling is analyzed. It shows that the tree grows twice as fast in comparison to the flooding schedule's one, indicating that the serial schedule propagates information twice as fast in the code's underlying graph. Furthermore, an asymptotic analysis of the serial schedule's convergence rate is done using the density evolution (DE) algorithm. Applied to various ensembles of LDPC codes, it shows that for long codes the serial schedule is expected to converge in half the number of iterations compared to the standard flooding schedule, when working near the ensemble's threshold. This observation is generally proved for the binary erasure channel (BEC) under some natural assumptions. Finally, an accompanying concentration theorem is proved. 相似文献
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针对多元低密度奇偶校验(LDPC)码译码复杂度高、时延大等问题,提出了一种基于硬信息的低复杂度多元LDPC译码算法.来自信道的接收信号在初始化时,先进行非均匀量化预处理.在迭代过程中,校验节点端只需传输单个比特的二进制硬可靠度信息至变量节点.在变量节点端,可靠度信息按比特位进行简单的累加和更新,无需任何的系数修正操作.同时,变量节点使用了全信息的方式将信息传输至与其相邻的校验节点.仿真结果显示,与基于比特可靠度(BRB)的多元LDPC译码算法相比,提出的算法在较低量化比特情况下,能获得约0.3 dB的译码性能增益,且译码复杂度更低. 相似文献
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Sunghwan Kim Min-Ho Jang Jong-Seon No Song-Nam Hong Dong-Joon Shin 《Communications, IEEE Transactions on》2008,56(7):1025-1031
In this paper, we analyze the sequential message- passing decoding algorithm of low-density parity-check (LDPC) codes by partitioning check nodes. This decoding algorithm shows better bit error rate (BER) performance than the conventional message-passing decoding algorithm, especially for the small number of iterations. Analytical results indicate that as the number of partitioned subsets of check nodes increases, the BER performance is improved. We also derive the recursive equations for mean values of messages at check and variable nodes by using density evolution with a Gaussian approximation. From these equations, the mean values are obtained at each iteration of the sequential decoding algorithm and the corresponding BER values are calculated. They show that the sequential decoding algorithm converges faster than the conventional one. Finally, the analytical results are confirmed by the simulation results. 相似文献
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针对中短码长的低密度奇偶校验规则码(Low Density Parity Check, LDPC)规则码,该文采用消息更新规则改进和因子图变换方法,提出一种低复杂度差分迭代译码算法。在置信传播算法的基础上,仅当变量节点的消息值振荡时引入差分映射策略,得出一种选择性的置信差分规则,自适应地调整校验节点消息的归一化系数,提高译码性能。同时,采用展开校验节点的图变换方法,将计算复杂度从随节点度分布指数性增长降至线性增长。分别在高斯白噪声信道和瑞利衰落信道下进行仿真实验,结果表明该算法和基于图变换的其他低复杂度译码算法相比,性能优越且复杂度低,和对数似然比的置信传播算法(LLR-BP)相比,高信噪比区域内的性能优异,低信噪比区域内的计算复杂度明显降低。 相似文献
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Shek F. Yau Tan L. Wong Francis C. M. Lau Yejun He 《Wireless Communications and Mobile Computing》2013,13(7):663-670
Low‐density parity‐check (LDPC) codes are very powerful error‐correction codes with capabilities approaching the Shannon's limits. In evaluating the error performance of an LDPC code, the computer simulation time taken becomes a primary concern when tens of millions of noise‐corrupted codewords are to be decoded, particularly for codes with very long lengths. In this paper, we propose modeling the parity‐check matrix of an LDPC code with compressed parity‐check matrices in the check‐node domain (CND) and in the bit‐node domain (BND), respectively. Based on the compressed parity‐check matrices, we created two message matrices, one in the CND and another in the BND, and two domain conversion matrices, one from CND to BND and another from BND to CND. With the proposed message matrices, the data used in the iterative LDPC decoding algorithm can be closely packed and stored within a small memory size. Consequently, such data can be mostly stored in the cache memory, reducing the need for the central processing unit to access the random access memory and hence improving the simulation time significantly. Furthermore, the messages in one domain can be easily converted to another domain with the use of the conversion matrices, facilitating the central processing unit to access and update the messages. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
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Optimization of scaling soft information in iterative decoding via density evolution methods 总被引:1,自引:0,他引:1
《Communications, IEEE Transactions on》2005,53(6):957-961
Density evolution has recently been used to analyze iterative decoding and explain many characteristics of iterative decoding including convergence of performance and preferred structures for the constituent codes. The scaling of extrinsic information (messages) has been heuristically used to enhance the performance in the iterative decoding literature, particularly based on the min-sum message passing algorithm. In this paper, it is demonstrated that density evolution can be used to obtain the optimal scaling factor and also estimate the maximum achievable scaling gain. For low density parity check (LDPC (codes and serially) concatenated convolutional codes (SCCC) with two-state constituent codes, the analytic density evolution technique is used, while the signal-to-noise ratio (SNR) evolution technique and the EXIT chart technique is used for SCCC with more than 2 state constituent codes. Simulation results show that the scaling gain predicted by density evolution or SNR evolution matches well with the scaling gain observed by simulation. 相似文献