LDPC码的全并行概率译码

针对LDPC码和积译码算法运算量大、电路实现复杂度高,介绍一种新的LDPC译码实现结构——概率译码器。该结构结合随机运算思想,运算量大幅降低,电路布线实现压力减小,吞吐量显著提高,针对该算法的内部路由可能出现的死锁问题引入了边存储器（EM,Edge Memory）概念。在AWGN信道下,对上述方法进行了仿真验证,给出了新方案和旧算法的性能分析比较,结果显示该算法的性能相比传统LDPC译码器有近0.2 dB的性能损失,但译码复杂度得到显著降低。     

DTMB中LDPC码编译码器的FPGA实现

针对数字地面多媒体广播标准中的低密度奇偶校验(LDPC)码,设计实现了基于现场可编程逻辑门阵列(FPGA)的LDPC码编译码器。设计所采用的编译码器方案均采用部分并行结构,在吞吐量与硬件复杂度之间达到了较好的折中。进一步,实现了用于LDPC码性能测试的误码测试硬件系统。基于FPGA的硬件实现结果表明,针对码率为0.4的LDPC码,设计的编译码器可工作在160MHz的时钟频率下,以译码前的数据量计算,吞吐量达到214Mbps。当误比特率为10-6时,实现的6比特量化译码器与浮点译码器的性能差距仅为0.05d B。     

基于FMS算法的多元LDPC码的译码器设计

多元LDPC码具有比二元LDPC码更好的应用前景,但是过高的译码复杂度限制了它在实际系统的中的应用。在扩展最小和(EMS)系列的译码算法中,固定路径最小和(FMS)译码算法不仅具有很低的复杂度,还具有良好的性能。针对如何实现低复杂度的多元LDPC译码器,对FMS算法和分层译码算法进行了介绍,对FMS算法和EMS算法的性能和复杂度进行了对比,最后基于FMS算法实现了一种具有分层结构的译码器。该译码器基于FPGA平台设计,具有较低的硬件资源占用。     

基于循环移位矩阵的LDPC码构造方法研究

论文提出了一种将矩阵分块并以单位阵的循环移位阵为基本单元构造LDPC码的校验矩阵的方法,降低了LDPC码在和积算法下的译码复杂度。同时,基于这种循环移位矩阵构造的类下三角结构可以减小编码复杂度。仿真和分析结果表明,这种LDPC码相对于随机构造的LDPC码在环长分布、最小汉明距离以及误码率性能方面也具有优越性。     

一种多模LDPC译码器的可重构结构

在分析低密度奇偶校验码(LDPC)算法的基础上,根据可重构思想,提出了一种支持12种模式LDPC的可重构结构。调用不同配置参数,重新组合译码器结构,实现可重构译码。利用接收到的移位配置信息,重构不同位宽的数据循环移位网络。采用NMS优化的TDMP算法,降低了系统硬件开销和系统级应用的复杂度,节省了芯片面积。该译码器基于TSMC 0.13 μm CMOS工艺进行设计。结果表明,该译码器的最大时钟频率达240 MHz,最高吞吐率达1.568 Gbit/s。相比于其他可重构结构的译码器,该译码器的芯片面积更小,支持的模式更多。     

基于矩阵分块的LDPC码快速编码结构研究

低密度奇偶校验(LDPC)码由于具有接近香农限的性能和高速并行的译码结构而成为研究热点。然而,当码长很长时,编译码器的硬件实现变得很困难。文章从编译码实际实现的角度出发,提出一种基于分块的LDPC码下三角形校验矩阵结构,降低了编译码复杂度,不仅可以实现线性时间编码,同时还可以实现部分并行译码。仿真结果表明,具有这种结构的LDPC码和随机构造的LDPC码相比具有同样好的纠错性能。     

低复杂度的LDPC码联合编译码构造方法研究

LDPC码因为其具有接近香农限的译码性能和适合高速译码的并行结构,已经成为纠错编码领域的研究热点。LDPC码校验矩阵的构造是基于稀疏的随机图,所以该类码字编码和译码的硬件实现比较复杂。以单位阵的循环移位阵为基本单元,构造LDPC码的校验矩阵,降低了LDPC码在和积算法下的译码复杂度。同时考虑到LDPC码的编码复杂度,给出了一种可以简化编码的结构。针对该方案构造的LDPC码,提出了消除其二分图上的短圈的方法。通过大量的仿真和计算分析,本文比较了这种LDPC码和随机构造的LDPC码在误码率性能,圈长分布以及最小码间距估计上的差异。     

基于AGC方法的软判决LDPC译码器输入匹配电路

针对低密度奇偶校验码(LDPC)译码器性能受输入软信息电平抖动影响较大的问题,本文提出一种基于自动增益控制(AGC)方法的输入匹配电路,能够跟踪输入的信号电平变化动态调整信号幅度,使解调器与LDPC译码器始终工作在最佳匹配状态.此方法及AGC结构匹配电路模块已用于实现高速超宽带(MBOK-UWB)无线通信系统接收机的LDPC译码器,系统仿真和实际测试结果均表明,上述方法有效提高了系统的误比特性能.     

CCSDS标准LDPC部分并行译码器实现

针对CCSDS标准中近地通信的LDPC码,为了提高准循环低密度奇偶校验（QC-LDPC）译码器的吞吐率和资源利用率,设计实现了一种低复杂度高速并行译码器。译码器整体采用流水线结构,通过改进校验节点与变量节点的更新方式,在不增加运算复杂度的情况下使信息处理所消耗的时间更短,压缩单次迭代所需时间,提高了译码器的吞吐量。以现场可编程门阵列（FPGA）作为实现平台,仿真并实现了基于归一化最小和算法的（8176,7154） LDPC译码器。结果表明,当译码器工作频率为200 MHz、迭代次数为10次的情况下,译码吞吐量可达到160 Mbit/s,满足大多数场景的应用需求。     

LDPC码全并行译码器的设计与实现

本论文用可编程逻辑器件(FPGA)实现了一种低密度奇偶校验码(LDPC)的编译码算法.采用基于Q矩阵LDPC码构造方法,设计了具有线性复杂度的编码器. 基于软判决译码规则,采用全并行译码结构实现了码率为1/2、码长为40比特的准规则LDPC码译码器,并且通过了仿真测试.该译码器复杂度与码长成线性关系,与Turbo码相比更易于硬件实现,并能达到更高的传输速率.     

Efficient Shuffle Network Architecture and Application for WiMAX LDPC Decoders

In this brief, a new algorithm that can efficiently generate all the control signals for the shuffle network used in flexible low-density parity-check (LDPC) decoders is proposed. Employing the proposed algorithm, the hardware complexity of the controller of shuffle networks using the Benes network structure can be significantly reduced. In addition, a low-complexity reconfigurable shuffle network architecture for flexible LDPC decoders is developed. Both the Benes network and the controller can be tailored to fit specific applications. Consequently, an efficient shuffle network for WiMAX LDPC decoders is presented. Synthesis results demonstrate that with the SMIC 0.18-$muhbox{m}$ complementary metal–oxide–semiconductor process, the total gate count of the proposed shuffle network is only 16 000. The area saving is between 26.6% and 71.1% compared to related works in the literature.      

High-throughput LDPC decoders

A high-throughput memory-efficient decoder architecture for low-density parity-check (LDPC) codes is proposed based on a novel turbo decoding algorithm. The architecture benefits from various optimizations performed at three levels of abstraction in system design-namely LDPC code design, decoding algorithm, and decoder architecture. First, the interconnect complexity problem of current decoder implementations is mitigated by designing architecture-aware LDPC codes having embedded structural regularity features that result in a regular and scalable message-transport network with reduced control overhead. Second, the memory overhead problem in current day decoders is reduced by more than 75% by employing a new turbo decoding algorithm for LDPC codes that removes the multiple checkto-bit message update bottleneck of the current algorithm. A new merged-schedule merge-passing algorithm is also proposed that reduces the memory overhead of the current algorithm for low to moderate-throughput decoders. Moreover, a parallel soft-input-soft-output (SISO) message update mechanism is proposed that implements the recursions of the Balh-Cocke-Jelinek-Raviv (BCJR) algorithm in terms of simple "max-quartet" operations that do not require lookup-tables and incur negligible loss in performance compared to the ideal case. Finally, an efficient programmable architecture coupled with a scalable and dynamic transport network for storing and routing messages is proposed, and a full-decoder architecture is presented. Simulations demonstrate that the proposed architecture attains a throughput of 1.92 Gb/s for a frame length of 2304 bits, and achieves savings of 89.13% and 69.83% in power consumption and silicon area over state-of-the-art, with a reduction of 60.5% in interconnect length.     

Implementation of a Flexible LDPC Decoder

Low-density parity-check codes (LDPC) are among the most powerful error correcting tools today available. For this reason they became very popular in several applications such as the digital satellite broadcasting system (DVB-S2), wireless local area network (IEEE 802.11n) and metropolitan area network (802.16e). Whereas several code-specific decoders have been proposed in the literature, the implementation of a high performance yet flexible LDPC decoder still is a challenging topic. This work presents a novel formulation of the decoding algorithm that strongly simplifies internal communication requirements and enables the development of decoders supporting generally defined LDPC codes. The resulting architecture is tailored to decode both IEEE 802.11n and IEEE 802.16e LDPC codes, as well as any other code of comparable complexity. The implementation cost deriving from the full flexibility offered by the proposed approach is also evaluated.     

Operation reduced low‐density parity‐check decoding algorithms for low power communication systems

Decoding operation reduction algorithms on min‐sum layered low‐density parity‐check (LDPC) decoders are proposed in this paper. Our algorithm freezes selected operations in high reliable nodes to reduce power while preserving error correcting performance. Both memory accesses and active node switching activities can be reduced. A novel node refresh mechanism reactivates frozen nodes to minimize coding gain degradation. We propose three decoding operation reduction algorithm variations to trade‐off complexity and operation reduction for LDPC decoders with different degrees of parallelism and memory requirement. Simulation results show that the number of LDPC decoding operations is reduced across all SNR ranges. The decoding convergence speed is not affected. Hardware architecture and FPGA implementation for IEEE 802.16e LDPC codes are presented. Copyright © 2011 John Wiley & Sons, Ltd.     

Resource efficient LDPC decoders for multimedia communication

Achieving high image quality is an important aspect in an increasing number of wireless multimedia applications. These applications require resource efficient error correction hardware to detect and correct errors introduced by the communication channel. This paper presents an innovative flexible architecture for error correction using Low-Density Parity-Check (LDPC) codes. The proposed partially-parallel decoder architecture utilizes a novel code construction technique based on multi-level Hierarchical Quasi-Cyclic (HQC) matrix. The proposed architecture is resource efficient, provides scalable throughput and requires substantially less power compared to other decoders reported to date. The proposed decoder has been implemented on a Xilinx FPGA suitable for WiMAX application and achieves a throughput of 548 Mbps. Performance evaluation of the decoder has been carried out by transmitting JPEG images over a wireless noisy channel and comparing the quality of the reconstructed images with those from other similar decoders.     

High-Throughput Layered LDPC Decoding Architecture

This paper presents a high-throughput decoder architecture for generic quasi-cyclic low-density parity-check (QC-LDPC) codes. Various optimizations are employed to increase the clock speed. A row permutation scheme is proposed to significantly simplify the implementation of the shuffle network in LDPC decoder. An approximate layered decoding approach is explored to reduce the critical path of the layered LDPC decoder. The computation core is further optimized to reduce the computation delay. It is estimated that 4.7 Gb/s decoding throughput can be achieved at 15 iterations using the current technology.      

Generic Description and Synthesis of LDPC Decoders

Through a rapid survey of the architecture of low-density parity-check (LDPC) decoders, this paper proposes a general framework to describe and compare the LDPC decoder architectures. A set of parameters makes it possible to classify the scheduling of iterative decoders, memory organization, and type of check-node processors and variable-node processors. Using the proposed framework, an efficient generic architecture for nonflooding schedules is also given.     

Design of LDPC decoders for improved low error rate performance: quantization and algorithm choices

Many classes of high-performance low-density parity-check (LDPC) codes are based on parity check matrices composed of permutation submatrices. We describe the design of a parallel-serial decoder architecture that can be used to map any LDPC code with such a structure to a hardware emulation platform. High-throughput emulation allows for the exploration of the low bit-error rate (BER) region and provides statistics of the error traces, which illuminate the causes of the error floors of the (2048, 1723) Reed-Solomon based LDPC (RS-LDPC) code and the (2209, 1978) array-based LDPC code. Two classes of error events are observed: oscillatory behavior and convergence to a class of non-codewords, termed absorbing sets. The influence of absorbing sets can be exacerbated by message quantization and decoder implementation. In particular, quantization and the log-tanh function approximation in sum-product decoders strongly affect which absorbing sets dominate in the errorfloor region. We show that conventional sum-product decoder implementations of the (2209, 1978) array-based LDPC code allow low-weight absorbing sets to have a strong effect, and, as a result, elevate the error floor. Dually-quantized sum-product decoders and approximate sum-product decoders alleviate the effects of low-weight absorbing sets, thereby lowering the error floor.     

A fast LDPC encoder/decoder for small/medium codes

Although Low-Density Parity-Check (LDPC) codes perform admirably for large block sizes — being mostly resilient to low levels of channel SNR and errors in channel equalization — real time operation and low computational effort require small and medium sized codes, which tend to be affected by these two factors. For these small to medium codes, a method for designing efficient regular codes is presented and a new technique for reducing the dependency of correct channel equalization, without much change in the inner workings or architecture of existing LDPC decoders is proposed. This goal is achieved by an improved intrinsic Log-Likelihood Ratio (LLR) estimator in the LDPC decoder — the ILE-Decoder, which only uses LDPC decoder-side information gathered during standard LDPC decoding. This information is used to improve the channel parameters estimation, thus improving the reliability of the code correction, while reducing the number of required iterations for a successful decoding. Methods for fast encoding and decoding of LDPC codes are presented, highlighting the importance of assuring low encoding/decoding latency with maintaining high throughput. The assumptions and rules that govern the estimation process via subcarrier corrected-bit accounting are presented, and the Bayesian inference estimation process is detailed. This scheme is suitable for application to multicarrier communications, such as OFDM. Simulation results in a PLC-like environment that confirm the good performance of the proposed LDPC coder/decoder are presented.     

Layered Approx-Regular LDPC: Code Construction and Encoder/Decoder Design

Layered approximately regular (LAR) low-density parity-check (LDPC) codes are proposed, with which one single pair of encoder and decoder support various code lengths and code rates. The parity check matrices of LAR-LDPC codes have a "layer-block-cell" structure with some additional constraints. An encoder architecture is then designed for LAR-LDPC codes, by making two improvements to the Richardson-Urbanke approach: the forward substitution operation is entirely removed and the dense-matrix-vector multiplication is handled using feedback shift-registers. A partially parallel decoder architecture is also designed for LAR-LDPC codes, where a layered modified min-sum decoding algorithm is used to trade off among complexity, speed, and performance. More importantly, the interconnection network, which is inevitable for partially parallel decoders, has much lower hardware complexity compared with that for general LDPC codes. Both the encoder and decoder architectures are highly flexible in code length and code rate.