一种低复杂度的多元LDPC译码算法

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.     

基于大数逻辑可译LDPC码的译码算法研究

本文提出两种基于可靠度的迭代大数逻辑译码算法,从以下两个方面降低译码复杂度:(1)校验节点使用伴随式信息处理,可节省外信息的计算操作;(2)变量节点使用伴随信息进行总信息的投票计数过程.结合非均匀量化技术,接收信号在判决门限附近获得更加精细的处理.此外,本文利用量化参数和列重比例信息对可靠度偏移方向和幅度进行了设计.仿真实验表明,本文提出的算法能够在很低的量化比特(3~4 bits)下有效工作,具有优良的译码性能和快速的收敛速度.     

低密度校验码BP译码算法中量化问题的研究

本文对低密度校验(LDPC)码BP译码算法的量化问题(主要是接收比特信号和中间变量)进行了研究.着重讨论了量化范围、量化级数、均匀和非均匀量化等因素对译码性能的影响,给出了LDPC码BP译码算法的一些实用性的结论.并进一步发现在对BP译码算法的中间变量进行高阶量化处理时,在高信噪比的情况下,能明显地减小译码的误码率,降低译码算法的错误平层,提高译码性能.     

Rice信道下LDPC码密度进化的研究

应用低密度奇偶校验(LDPC)码译码消息的密度进化可以得到码集的噪声门限,依此评价不同译码算法的性能,并可以用来优化非正则LDPC码的次数分布对。该文首先以Rice信道下正则LDPC码为例,讨论了不同量化阶数及步长时BP,BP-based 和offset BP-based 3种译码算法的DDE(Discrete Density Evolution)分析,接着在offset BP-based译码算法的DDE分析基础上,采用差分进化方法对Rice信道下非正则LDPC码的次数分布对进行了优化,得出了相应的噪声门限。最后,给出了Rice信道下码率为1/2的优化非正则LDPC码的概率聚集函数(PMF)进化曲线。     

Low Complexity Decoder Architecture for Low-Density Parity-Check Codes

In this paper, we propose a low complexity decoder architecture for low-density parity-check (LDPC) codes using a variable quantization scheme as well as an efficient highly-parallel decoding scheme. In the sum-product algorithm for decoding LDPC codes, the finite precision implementations have an important tradeoff between decoding performance and hardware complexity caused by two dominant area-consuming factors: one is the memory for updated messages storage and the other is the look-up table (LUT) for implementation of the nonlinear function Ψ(x). The proposed variable quantization schemes offer a large reduction in the hardware complexities for LUT and memory. Also, an efficient highly-parallel decoder architecture for quasi-cyclic (QC) LDPC codes can be implemented with the reduced hardware complexity by using the partially block overlapped decoding scheme and the minimized power consumption by reducing the total number of memory accesses for updated messages. For (3, 6) QC LDPC codes, our proposed schemes in implementing the highly-parallel decoder architecture offer a great reduction of implementation area by 33% for memory area and approximately by 28% for the check node unit and variable node unit computation units without significant performance degradation. Also, the memory accesses are reduced by 20%.     

Nonuniform Encoding and Hybrid Decoding Schemes for Equal Error Protection of Rateless Codes

Messages are generally selected with the same probability in the encoding scheme of rateless codes for equal error protection. In addition, a belief propagation (BP) decoding scheme is generally used because of the low computational complexity. However, the probability of recovering a new message by BP decoding is reduced if both the recovered and unrecovered messages are selected uniformly. Thus, more codeword symbols than expected are required for the perfect recovery of message symbols. Therefore, a new encoding scheme with a nonuniform selection of messages is proposed in this paper. In addition, a BP‐Gaussian elimination hybrid decoding scheme that complements the drawback of the BP decoding scheme is proposed. The performances of the proposed schemes are analyzed and compared with those of the conventional schemes.     

An area efficient and high throughput multi-rate quasi-cyclic LDPC decoder for IEEE 802.11n applications

In this paper, an area efficient and high throughput multi-rate quasi-cyclic low-density parity-check (QC-LDPC) decoder for IEEE 802.11n applications is proposed. An overlapped message passing scheme and the non-uniform quantization scheme are incorporated to reduce the overall area and power of the proposed QC-LDPC decoder. In order to enhance the decoding throughput and reduce the size of memories storing soft messages, an improved early termination (ET) scheme and base matrix reordering technique is employed. These techniques significantly reduce the total number of decoding iterations and memory accessing conflicts without mitigating the decoding performance. Equipped with these techniques an area efficient and high throughput multi-rate QC-LDPC decoder is designed, simulated and implemented with Xilinx Virtex6 (XC6VLX760-2FF1760) for an irregular LDPC code of length 1944 and code rates (1/2–5/6) specified in IEEE 802.11n standard. With a maximum clock frequency of 574.136–587.458 MHz the proposed QC-LDPC decoder can achieve throughput in the range of 1.27–2.17 Gb/s for 10 decoding iterations. Furthermore, by using Cadence RTL compiler with UMC 130 nm VLSI technology, the core area of the proposed QC-LDPC decoder is found to be 1.42 mm² with a power dissipation in the range of 101.25–140.42 mW at 1.2 V supply voltage.     

低密度校验码量化译码研究

介绍了基于置信传播算法的LDPC码和积译码算法，分析其密度进行化特性，对不同消息空间中的量化译码问题进行研究，对采用不同量化方案时LDPC码在AWGN信道下的译码性能进行了仿真。仿真结果表明相对连续译码，中间变量6bit均匀量化会带来约0．4dB左右的损失，而10bit非均匀量化性能明显得到改善。合适的高阶量化译码可以获得接近连续译码的性能。     

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.     

一种联合星座和伴随式信息的迭代译码算法

针对构造性的大数逻辑可译低密度奇偶校验(LDPC)码,联合信号星座和伴随式信息,提出一种基于可靠度的迭代大数逻辑译码算法。在校验节点,直接使用伴随式信息进行传递和处理;在变量节点,结合信源端的星座映射和伴随式进行译码信息收集和处理。理论分析和仿真实验结果表明,所提出的算法在保持优良译码性能的同时,具有更低的译码复杂度。     

Min-Sum Decoder Architectures With Reduced Word Length for LDPC Codes

In this paper, we propose an improvement of the normalized min-sum (MS) decoding algorithm and novel MS decoder architectures with reduced word length using nonuniform quantization schemes for low-density parity-check (LDPC) codes. The proposed normalized MS algorithm introduces a more exact adjustment with two optimized correction factors for check-node-updating computations, while the conventional normalized MS algorithm applies only one correction factor. The proposed algorithm provides a significant performance gain without any additional computation or hardware complexity. The finite word-length analysis in implementing an LDPC decoder is a very important factor since it directly impacts the size of memory to store the intrinsic and extrinsic messages and the overall hardware area in the partially parallel LDPC decoder. The proposed nonuniform quantization scheme can reduce the finite word length while achieving similar performances compared to a conventional quantization scheme. From simulation results, it is shown that the proposed 4-bit nonuniform quantization scheme achieves an acceptable decoding performance, unlike the conventional 4-bit uniform quantization scheme. Finally, the proposed MS decoder architectures by the nonuniform quantization scheme provide significant reductions of 20% and up to 8% for the memory area and combinational logic area, respectively, compared to the conventional 5-bit ones.      

基于二元译码信息的迭代大数逻辑LDPC译码算法及其量化优化

该文提出一种低复杂度的迭代大数逻辑LDPC译码算法,在迭代过程中所有的译码信息都以二元形式进行传递、处理和迭代更新。所提算法不需要计算外信息,而是利用Tanner图上伴随式的对错状态来评判节点可靠度。与现有的几种迭代大数逻辑译码算法相比,该文算法也不需要信息修正处理,避免了相应的实数乘法操作,具有很低的译码复杂度。此外,该文引入一种特殊的量化处理函数,并给出了基于离散密度进化的参数优化过程。实验仿真表明,该文所提算法与原算法相比,在AWGN信道下可获得约0.3~0.4 dB的性能提升。同时,由于节点间交换传递的译码信息都是基于1个比特位的二元信息,也非常便于硬件的设计与实现。     

瑞利信道下基于广义阈值函数的LDPC译码算法

现存的LDPC译码算法,其节点处理依据主要遵循大数逻辑准则和完全处理准则,对应的阈值参数一般是固定不变的,在性能和复杂度之间的均衡不够灵活.本文首先提出一种广义阈值函数,能应用于大多数基于可靠度的二元LDPC译码算法.通过调整阈值参数,可方便地控制参与迭代处理的节点队列.其次,本文提出一种基于伴随式和星座映射信息的非均匀量化译码算法,可进一步降低复杂度和存储负荷.实验结果显示,在瑞利信道下,本文算法能够在较低的量化比特下获得优良的译码性能;结合广义阈值函数,只有约30%的变量节点参与迭代运算,译码复杂度可显著降低.     

一种交叠的Shuffled-BP LDPC译码算法

Shuffled-BP(SBP)译码算法是一种基于变量节点的串行消息传递译码算法,其收敛速度快于原有的置信度传播译码算法,然而由于实际工程实现中的半并行化处理,其收敛速度和误码性能均有所降低。为了进一步提高SBP算法的性能,该文提出一种交叠的Shuffled-BP(Overlapped Shuffled-BP, OSBP)译码算法。该算法采用若干个相同的子译码器以不同的更新顺序同时进行更新,对于每个变量节点,在每次迭代更新后选取最可靠的信息参与下一次迭代,以此提高迭代的收敛速度。理论分析和仿真实验均表明,在不增加额外存储空间的条件下,OSBP算法相比于SBP算法有着更优的误码性能以及更快的收敛速度。此外,提出的OSBP算法对于规则和不规则LDPC码均有效。     

A more accurate one-dimensional analysis and design of irregular LDPC codes

We introduce a new one-dimensional (1-D) analysis of low-density parity-check (LDPC) codes on additive white Gaussian noise channels which is significantly more accurate than similar 1-D methods. Our method assumes a Gaussian distribution in message-passing decoding only for messages from variable nodes to check nodes. Compared to existing work, which makes a Gaussian assumption both for messages from check nodes and from variable nodes, our method offers a significantly more accurate estimate of convergence behavior and threshold of convergence. Similar to previous work, the problem of designing irregular LDPC codes reduces to a linear programming problem. However, our method allows irregular code design in a wider range of rates without any limit on the maximum variable-node degree. We use our method to design irregular LDPC codes with rates greater than 1/4 that perform within a few hundredths of a decibel from the Shannon limit. The designed codes perform almost as well as codes designed by density evolution.     

An Improvement of UMP‐BP Decoding Algorithm Using the Minimum Mean Square Error Linear Estimator

In this paper, we propose the modified uniformly most powerful (UMP) belief‐propagation (BP)‐based decoding algorithm which utilizes multiplicative and additive factors to diminish the errors introduced by the approximation of the soft values given by a previously proposed UMP BP‐based algorithm. This modified UMP BP‐based algorithm shows better performance than that of the normalized UMP BP‐based algorithm, i.e., it has an error performance closer to BP than that of the normalized UMP BP‐based algorithm on the additive white Gaussian noise channel for low density parity check codes. Also, this algorithm has the same complexity in its implementation as the normalized UMP BP‐based algorithm.     

失真补偿量化索引调制水印的性能分析

该文分析了基于量化索引调制的失真补偿水印方案中量化步长的伸缩因子与失真度、鲁棒性和检测误码率之间的关系。在高分辨率量化的假设前提下,推导出失真补偿量化索引调制水印算法在加性高斯白噪声信道下的误码率计算公式,并提出了一个失真-鲁棒性函数来度量算法的抗噪鲁棒性和失真度与鲁棒性之间的代价关系。通过计算机仿真,比较了不同失真补偿量化索引调制水印方案下算法的失真-鲁棒性能和误码率性能;并以一段音频数据三级小波细节系数为载体嵌入水印信息,统计检测时的位错误率。实验结果验证了在低量化步长范围内,理论预测误码率与实验检测误码率较为吻合,失真-鲁棒性函数能够很好地度量高分辨率量化前提下的算法抗噪鲁棒性和失真度与鲁棒性之间的代价关系。     

Improving belief propagation on graphs with cycles

In this letter, we propose two modifications to belief propagation (BP) decoding algorithm. The modifications are based on reducing the reliability of messages throughout the iteration process, and are particularly effective for short low-density parity-check codes, where the existence of cycles makes the original BP algorithm perform suboptimal. The proposed algorithms, referred to as "normalized BP" and "offset BP," reduce the absolute value of the outgoing log-likelihood ratio messages at variable nodes by using a multiplicative factor and an additive factor, respectively. Simulation results show that both algorithms perform more or less the same, and both outperform BP in error performance.     

基于高斯消元的BATS码的改进译码算法

BATS码是一种包括外码和内码的纠删码,外码是喷泉码的矩阵形式。内码是网络编码结构,采用随机线性网络编码算法。BATS码的常用译码算法为BP译码算法,但对有限长BATS码,BP译码算法的性能有大幅度的衰减。因此,在计算资源充足的情况下,可以在BP译码器后采用高斯消元算法对BATS码进行译码。采用高斯消元算法时,矩阵满秩则输入数据包可译,反之则不可译。因此,利用当矩阵不满秩时也有部分包可译的特点,识别并将这部分可译包译出,从而提高高斯消元译码器的译码性能。     

一种基于量化预处理的低复杂度LDPC译码算法

为了降低低密度奇偶校验(Low Density Parity Check,LDPC)码译码算法的复杂度,提出了一种基于量化预处理的LDPC迭代大数逻辑译码算法。该算法在迭代译码过程中,校验节点采用基于伴随式的信息处理方式,避免了外信息的计算;同时,变量节点基于回传的伴随式信息进行可靠度偏移大小的计算,并结合与当前码位相对应的调制映射信息进行可靠度偏移方向的设计。迭代更新时,变量节点采用基于信息匹配的可靠度更新规则。迭代前的量化预处理能避免实数乘法运算进入迭代过程,使其只涉及整数加法操作和逻辑操作。仿真结果表明,在保持译码性能的前提上,所提算法具有更低的译码复杂度。