A Flexible LDPC/Turbo Decoder Architecture

Low-density parity-check (LDPC) codes and convolutional Turbo codes are two of the most powerful error correcting codes that are widely used in modern communication systems. In a multi-mode baseband receiver, both LDPC and Turbo decoders may be required. However, the different decoding approaches for LDPC and Turbo codes usually lead to different hardware architectures. In this paper we propose a unified message passing algorithm for LDPC and Turbo codes and introduce a flexible soft-input soft-output (SISO) module to handle LDPC/Turbo decoding. We employ the trellis-based maximum a posteriori (MAP) algorithm as a bridge between LDPC and Turbo codes decoding. We view the LDPC code as a concatenation of n super-codes where each super-code has a simpler trellis structure so that the MAP algorithm can be easily applied to it. We propose a flexible functional unit (FFU) for MAP processing of LDPC and Turbo codes with a low hardware overhead (about 15% area and timing overhead). Based on the FFU, we propose an area-efficient flexible SISO decoder architecture to support LDPC/Turbo codes decoding. Multiple such SISO modules can be embedded into a parallel decoder for higher decoding throughput. As a case study, a flexible LDPC/Turbo decoder has been synthesized on a TSMC 90 nm CMOS technology with a core area of 3.2 mm². The decoder can support IEEE 802.16e LDPC codes, IEEE 802.11n LDPC codes, and 3GPP LTE Turbo codes. Running at 500 MHz clock frequency, the decoder can sustain up to 600 Mbps LDPC decoding or 450 Mbps Turbo decoding.     

FPGA implementation of low complexity LDPC iterative decoder

Low-density parity-check (LDPC) codes, proposed by Gallager, emerged as a class of codes which can yield very good performance on the additive white Gaussian noise channel as well as on the binary symmetric channel. LDPC codes have gained lots of importance due to their capacity achieving property and excellent performance in the noisy channel. Belief propagation (BP) algorithm and its approximations, most notably min-sum, are popular iterative decoding algorithms used for LDPC and turbo codes. The trade-off between the hardware complexity and the decoding throughput is a critical factor in the implementation of the practical decoder. This article presents introduction to LDPC codes and its various decoding algorithms followed by realisation of LDPC decoder by using simplified message passing algorithm and partially parallel decoder architecture. Simplified message passing algorithm has been proposed for trade-off between low decoding complexity and decoder performance. It greatly reduces the routing and check node complexity of the decoder. Partially parallel decoder architecture possesses high speed and reduced complexity. The improved design of the decoder possesses a maximum symbol throughput of 92.95 Mbps and a maximum of 18 decoding iterations. The article presents implementation of 9216 bits, rate-1/2, (3, 6) LDPC decoder on Xilinx XC3D3400A device from Spartan-3A DSP family.     

Highly-Parallel Decoding Architectures for Convolutional Turbo Codes

Highly parallel decoders for convolutional turbo codes have been studied by proposing two parallel decoding architectures and a design approach of parallel interleavers. To solve the memory conflict problem of extrinsic information in a parallel decoder, a block-like approach in which data is written row-by-row and read diagonal-wise is proposed for designing collision-free parallel interleavers. Furthermore, a warm-up-free parallel sliding window architecture is proposed for long turbo codes to maximize the decoding speeds of parallel decoders. The proposed architecture increases decoding speed by 6%-34% at a cost of a storage increase of 1% for an eight-parallel decoder. For short turbo codes (e.g., length of 512 bits), a warm-up-free parallel window architecture is proposed to double the speed at the cost of a hardware increase of 12%     

Optimal Overlapped Message Passing Decoding of Quasi-Cyclic LDPC Codes

Efficient hardware implementation of low-density parity-check (LDPC) codes is of great interest since LDPC codes are being considered for a wide range of applications. Recently, overlapped message passing (OMP) decoding has been proposed to improve the throughput and hardware utilization efficiency (HUE) of decoder architectures for LDPC codes. In this paper, we first study the scheduling for the OMP decoding of LDPC codes, and show that maximizing the throughput gain amounts to minimizing the intra- and inter-iteration waiting times. We then focus on the OMP decoding of quasi-cyclic (QC) LDPC codes. We propose a partly parallel OMP decoder architecture and implement it using FPGA. For any QC LDPC code, our OMP decoder achieves the maximum throughput gain and HUE due to overlapping, hence has higher throughput and HUE than previously proposed OMP decoders while maintaining the same hardware requirements. We also show that the maximum throughput gain and HUE achieved by our OMP decoder are ultimately determined by the given code. Thus, we propose a coset-based construction method, which results in QC LDPC codes that allow our optimal OMP decoder to achieve higher throughput and HUE.     

Semi-Iterative Analog Turbo Decoding

Based on multiple-slice turbo codes, a novel semi-iterative analog turbo decoding algorithm and its corresponding decoder architecture are presented. This work paves the way for integrating flexible analog decoders dealing with frame lengths over thousands of bits. The algorithm benefits from a partially continuous exchange of extrinsic information to improve decoding speed and correction performance. The proposed algorithm and architecture are applied to design an analog decoder for double-binary codes. Taking full advantage of multiple slice codes, the on-chip area is shown to be reduced by ten when compared to a conventional fully parallelized analog slice turbo decoder. The reconfigurable analog core area for frames of 40 bits up to 2432 bits is 37 nm² in a 0.25-mum BiCMOS process.     

Switching Activity Minimization in Iterative LDPC Decoders

LDPC codes can be designed to perform extremely close to the Shannon limit. Achieving such performance with high energy efficiency is now a main goal in the research community. This work combines knowledge of LDPC decoder message statistics, provided by density evolution, with knowledge of the physical implementation of decoders to predict switching activity in the decoder interconnect. In this work we provide results for the switching activity on the interconnect for fully parallel decoders. However, our model can be applied to partially parallel and serial implementations, and is not limited to interconnect. It is shown that switching activity can vary by as much as 300%, depending on several hardware design choices. Results of this work validate the usefulness of the presented model for providing designers with an understanding of how their decoder implementation choices affect power consumption for any size of LDPC code. This knowledge can be used for making design choices that minimize decoder power consumption very early in the hardware design process.     

A Memory Efficient Partially Parallel Decoder Architecture for Quasi-Cyclic LDPC Codes

This paper presents a memory efficient partially parallel decoder architecture suited for high rate quasi-cyclic low-density parity-check (QC-LDPC) codes using (modified) min-sum algorithm for decoding. In general, over 30% of memory can be saved over conventional partially parallel decoder architectures. Efficient techniques have been developed to reduce the computation delay of the node processing units and to minimize hardware overhead for parallel processing. The proposed decoder architecture can linearly increase the decoding throughput with a small percentage of extra hardware. Consequently, it facilitates the applications of LDPC codes in area/power sensitive high-speed communication systems     

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.     

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.     

High performance, high throughput turbo/SOVA decoder design

Two efficient approaches are proposed to improve the performance of soft-output Viterbi (1998) algorithm (SOVA)-based turbo decoders. In the first approach, an easily obtainable variable and a simple mapping function are used to compute a target scaling factor to normalize the extrinsic information output from turbo decoders. An extra coding gain of 0.5 dB can be obtained with additive white Gaussian noise channels. This approach does not introduce extra latency and the hardware overhead is negligible. In the second approach, an adaptive upper bound based on the channel reliability is set for computing the metric difference between competing paths. By combining the two approaches, we show that the new SOVA-based turbo decoders can approach maximum a posteriori probability (MAP)-based turbo decoders within 0.1 dB when the target bit-error rate (BER) is moderately low (e.g., BER<10/sup -4/ for 1/2 rate codes). Following this, practical implementation issues are discussed and finite precision simulation results are provided. An area-efficient parallel decoding architecture is presented in this paper as an effective approach to design high-throughput turbo/SOVA decoders. With the efficient parallel architecture, multiple times throughput of a conventional serial decoder can be obtained by increasing the overall hardware by a small percentage. To resolve the problem of multiple memory accesses per cycle for the efficient parallel architecture, a novel two-level hierarchical interleaver architecture is proposed. Simulation results show that the proposed interleaver architecture performs as well as random interleavers, while requiring much less storage of random patterns.     

A 0.18-$muhbox m$CMOS Analog Min-Sum Iterative Decoder for a (32,8) Low-Density Parity-Check (LDPC) Code

Current-mode circuits are presented for implementing analog min-sum (MS) iterative decoders. These decoders are used to efficiently decode the best known error correcting codes such as low-density parity-check (LDPC) codes and turbo codes. The proposed circuits are devised based on current mirrors, and thus, in any fabrication technology that accurate current mirrors can be designed, analog MS decoders can be implemented. The functionality of the proposed circuits is verified by implementing an analog MS decoder for a (32,8) LDPC code in a 0.18-mum CMOS technology. This decoder is the first reported analog MS decoder. For low signal to noise ratios where the circuit imperfections are dominated by the noise of the channel, the measured error correcting performance of this chip in steady-state condition surpasses that of the conventional floating-point discrete-time synchronous MS decoder. When data throughput is 6 Mb/s, loss in the coding gain compared to the conventional MS decoder at BER of 10^-3 is about 0.3 dB and power consumption is about 5 mW. This is the first time that an analog decoder has been successfully tested for an LDPC code, though a short one     

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.     

Turbo decoder

We propose an adaptive channel SNR estimation algorithm required for the iterative MAP decoding of turbo decoders. The proposed algorithm uses the extrinsic values generated within the iterative MAP decoder to update the channel SNR estimate toward its optimum value per each decoder iteration or per each turbo code frame     

基于FFT-BP算法的多元域LDPC码译码器设计与FPGA实现

GF(q)域上的LDPC码是二进制LDPC码的扩展,它具有比二进制LDPC码更好的纠错性能。FFT-BP算法是高效的LDPC码译码算法,本文在GF(4)域上探讨该算法的设计与实现。本文的创新之处在于,根据FFT-BP算法的特点设计了一种利用Tanner图进行信息索引的方式,简化了地址查询模块的设计。实验表明,在归一化信噪比为2.6dB时,译码器的误码率可达到10-6。     

An Efficient VLSI Architecture for Nonbinary LDPC Decoders

Low-density parity-check (LDPC) codes constructed over the Galois field $ hbox{GF}(q)$, which are also called nonbinary LDPC codes, are an extension of binary LDPC codes with significantly better performance. Although various kinds of low-complexity quasi-optimal iterative decoding algorithms have been proposed, the VLSI implementation of nonbinary LDPC decoders has rarely been discussed due to their hardware unfriendly properties. In this brief, an efficient selective computation algorithm, which totally avoids the sorting process, is proposed for Min–Max decoding. In addition, an efficient VLSI architecture for a nonbinary Min–Max decoder is presented. The synthesis results are given to demonstrate the efficiency of the proposed techniques.      

多码率LDPC码高速译码器的设计与实现

低密度奇偶校验码(LDPC码)以其接近香浓极限的性能得到了广泛的应用.如何在.FPGA上实现多码率LDPC码的高速译码,则是LDPC码应用的一个焦点.本文介绍了一种多码率LDPC码及其简化的和积译码算法;设计了这种多码率LDPC码的高速译码器,该译码器拥有半并行的运算结构和不同码率码共用相同的存储单元的存储资源利用结构,并以和算法与积算法功能单元同时工作的机制交替完成对两个码字的译码,提高了资源利用率和译码速率.最后,本文采用该结构在FPGA平台上实现了码长8064比特码率7/8、6/8、5/8、4/8、3/8五个码率的多码率LDPC码译码器.测试结果表明,译码器的有效符号速率达到200Mbps.     

RS码与LDPC码的联合迭代译码

针对RS码与LDPC码的串行级联结构,提出了一种基于自适应置信传播(ABP)的联合迭代译码方法.译码时,LDPC码置信传播译码器输出的软信息作为RS码ABP译码器的输入;经过一定迭代译码后,RS码译码器输出的软信息又作为LDPC译码器的输入.软输入软输出的RS译码器与LDPC译码器之间经过多次信息传递,译码性能有很大提高.码长中等的LDPC码采用这种级联方案,可以有效克服短环的影响,消除错误平层.仿真结果显示:AWGN信道下这种基于ABP的RS码与LDPC码的联合迭代译码方案可以获得约0.8 dB的增益.     

The Development of Turbo and LDPC Codes for Deep-Space Applications

The development of error-correcting codes has been closely coupled with deep-space exploration since the early days of both. Since the discovery of turbo codes in 1993, the research community has invested a great deal of work on modern iteratively decoded codes, and naturally NASA's Jet Propulsion Laboratory (JPL) has been very much involved. This paper describes the research, design, implementation, and standardization work that has taken place at JPL for both turbo and low-density parity-check (LDPC) codes. Turbo code development proceeded from theoretical analyses of polynomial selection, weight distributions imposed by interleaver designs, decoder error floors, and iterative decoding thresholds. A family of turbo codes was standardized and implemented and is currently in use by several spacecraft. JPL's LDPC codes are built from protographs and circulants, selected by analyses of decoding thresholds and methods to avoid loops in the code graph. LDPC encoders and decoders have been implemented in hardware for planned spacecraft, and standardization is under way.     

Configurable Multi-Rate Decoder Architecture for QC-LDPC Codes Based Broadband Broadcasting System

In this paper we present a Base-matrix based decoder architecture for multi-rate QC-LDPC codes proposed in broadband broadcasting system. We use the Modified Min-Sum Algorithm (MMSA) as the decoding algorithm in this architecture, which lowers the complexity of the LDPC decoder while keeping almost the same performance or even better. Based on this algorithm, we designed a novel check node processing unit to reduce the complexity of the decoder and facilitate the multiplex of the processing units. The decoder designed with hardware constraints is not only scalable in throughput, but also easily configurable to support different QC-LDPC codes flexible in code rate and code length.     

A 690-mW 1-Gb/s 1024-b, rate-1/2 low-density parity-check codedecoder

A 1024-b, rate-1/2, soft decision low-density parity-check (LDPC) code decoder has been implemented that matches the coding gain of equivalent turbo codes. The decoder features a parallel architecture that supports a maximum throughput of 1 Gb/s while performing 64 decoder iterations. The parallel architecture enables rapid convergence in the decoding algorithm to be translated into low decoder switching activity resulting in a power dissipation of only 690 mW from a 1.5-V supply