Applications of algebraic soft-decision decoding of Reed-Solomon codes

Efficient soft-decision decoding of Reed-Solomon (RS) codes is made possible by the Koetter-Vardy (KV) algorithm which consists of a front-end to the interpolation-based Guruswami-Sudan (GS) list decoding algorithm. This paper approaches the soft-decision KV algorithm from the point of view of a communications systems designer who wants to know what benefits the algorithm can give, and how the extra complexity introduced by soft decoding can be managed at the systems level. We show how to reduce the computational complexity and memory requirements of the soft-decision front-end. Applications to wireless communications over Rayleigh fading channels and magnetic recording channels are proposed. For a high-rate RS(255,239) code, 2-3 dB of soft-decision gain is possible over a Rayleigh fading channel using 16-quadrature amplitude modulation. For shorter codes and at lower rates, the gain can be as large as 9 dB. To lower the complexity of decoding on the systems level, the redecoding architecture is explored, which uses only the appropriate amount of complexity to decode each packet. An error-detection criterion based on the properties of the KV decoder is proposed for the redecoding architecture. Queueing analysis verifies the practicality of the redecoding architecture by showing that only a modestly sized RAM buffer is required.     

RS码译码算法对比研究

RS码所具有的高效译码性能使其被广泛应用于数据通信和存储系统的差错控制中。本文主要对目前常用的RS码的硬判决译码算法和K—V代数软判决译码算法进行对比研究。通过对两种算法原理的理论分析,给出了RS码在硬判决与软判决的算法下的计算机仿真。结果表明两种算法均能得到良好的译码效果,而软判决译码算法较硬判决方式能更有效地带来系统增益。而软判决译码算法可以通过适当提高复杂度来改善系统的性能。     

Soft-decision list decoding of hermitian codes

This paper proposes the first complete soft-decision list decoding algorithm for Hermitian codes based on the Koetter- Vardy's Reed-Solomon code decoding algorithm. For Hermitian codes, interpolation processes trivariate polynomials which are defined over the pole basis of a Hermitian curve. In this paper, the interpolated zero condition of a trivariate polynomial with respect to a multiplicity matrix M is redefined followed by a proof of the validity of the soft-decision scheme. This paper also introduces a new stopping criterion for the algorithm that tranforms the reliability matrix ? to the multiplicity matrix M. Geometric characterisation of the trivariate monomial decoding region is investigated, resulting in an asymptotic optimal performance bound for the soft-decision decoder. By defining the weighted degree upper bound of the interpolated polynomial, two complexity reducing modifications are introduced for the soft-decision scheme: elimination of unnecessary interpolated polynomials and pre-calculation of the coefficients that relate the pole basis monomials to the zero basis functions of a Hermitian curve. Our simulation results and analyses show that soft-decision list decoding of Hermitian code can outperform Koetter-Vardy decoding of Reed-Solomon code which is defined in a larger finite field, but with less decoding complexity.     

Efficient VLSI Architecture for Soft-Decision Decoding of Reed–Solomon Codes

Reed–Solomon (RS) codes have very broad applications in digital communication and storage systems. The recently developed algebraic soft-decision decoding (ASD) algorithms of RS codes can achieve substantial coding gain with polynomial complexity. Among the ASD algorithms with practical multiplicity assignment schemes, the bit-level generalized minimum distance (BGMD) decoding algorithm can achieve similar or higher coding gain with lower complexity. ASD algorithms consist of two major steps: the interpolation and the factorization. In this paper, novel architectures for both steps are proposed for the BGMD decoder. The interpolation architecture is based on the newly proposed Lee-O'Sullivan (LO) algorithm. By exploiting the characteristics of the LO algorithm and the multiplicity assignment scheme in the BGMD decoder, the proposed interpolation architecture for a (255, 239) RS code can achieve 25% higher efficiency in terms of speed/area ratio than prior efforts. Root computation over finite fields and polynomial updating are the two main steps of the factorization. A low-latency and prediction-free scheme is introduced in this paper for the root computation in the BGMD decoder. In addition, novel coefficient storage schemes and parallel processing architectures are developed to reduce the latency of the polynomial updating. The proposed factorization architecture is 126% more efficient than the previous direct root computation factorization architecture.      

Applications of Algebraic Soft-Decision Decoding of Reed–Solomon Codes

Efficient soft-decision decoding of Reed–Solomon codes is made possible by the Koetter–Vardy (KV) algorithm which consists of a front-end to the interpolation-based Guruswami–Sudan list decoding algorithm. This paper approaches the soft-decision KV algorithm from the point of view of a communications systems designer who wants to know what benefits the algorithm can give, and how the extra complexity introduced by soft decoding can be managed at the systems level. We show how to reduce the computational complexity and memory requirements of the soft-decision front-end. Applications to wireless communications over Rayleigh fading channels and magnetic recording channels are proposed. For a high-rate (RS 9225,239) Reed–Solomon code, 2–3 dB of soft-decision gain is possible over a Rayleigh fading channel using 16-quadrature amplitude modulation. For shorter codes and at lower rates, the gain can be as large as 9 dB. To lower the complexity of decoding on the systems level, the redecoding architecture is explored which uses only the appropriate amount of complexity to decode each packet. An error-detection criterion based on the properties of the KV decoder is proposed for the redecoding architecture. Queuing analysis verifies the practicality of the redecoding architecture by showing that only a modestly sized RAM buffer is required.     

Performance Analysis of Algebraic Soft-Decision Decoding of Reed–Solomon Codes

We investigate the decoding region for algebraic soft-decision decoding (ASD) of Reed–Solomon (RS) codes in a discrete, memoryless, additive-noise channel. An expression is derived for the error correction radius within which the soft-decision decoder produces a list that contains the transmitted codeword. The error radius for ASD is shown to be larger than that of Guruswami–Sudan (GS) hard-decision decoding for a subset of low and medium-rate codes. These results are also extended to multivariable interpolation in the sense of Parvaresh and Vardy.      

Fast decoding of the Leech lattice

An efficient algorithm is presented for maximum-likelihood soft-decision decoding of the Leech lattice. The superiority of this decoder with respect to both computational and memory complexities is demonstrated in comparison with previously published decoding methods. Gain factors in the range of 2-10 are achieved. The authors conclude with some more advanced ideas for achieving a further reduction of the algorithm complexity based on a generalization of the Wagner decoding method to two parity constraints. A comparison with the complexity of some trellis-coded modulation schemes is discussed. The decoding algorithm presented seems to achieve a computational complexity comparable to that of the equivalent trellis codes     

Algebraic analog decoding of linear binary codes

Bit-by-bit soft-decision decoding of binary cyclic codes is considered. A significant reduction in decoder complexity can be achieved by requiring only that the decoder correct all analog error patterns which fall within a Euclidean sphere whose radius is equal to half the minimum Euclidean distance of the code. Such a "maximum-radius" scheme is asymptotically optimum for the additive white Gaussian noise (AWGN) channel. An iterative extension of the basic algebraic analog decoding scheme is discussed, and performance curves are given for the (17,9), (21,11), and (73,45) codes on the AWGN channel.     

Reduced Complexity Interpolation Architecture for Soft-Decision Reed–Solomon Decoding

Reed-Solomon (RS) codes are one of the most widely utilized block error-correcting codes in modern communication and computer systems. Compared to hard-decision decoding, soft-decision decoding offers considerably higher error-correcting capability. The Koetter-Vardy (KV) soft-decision decoding algorithm can achieve substantial coding gain, while maintaining a complexity polynomial with respect to the code word length. In the KV algorithm, the interpolation step dominates the decoding complexity. A reduced complexity interpolation architecture is proposed in this paper by eliminating the polynomial updating corresponding to zero discrepancy coefficients in this step. Using this architecture, an area reduction of 27% can be achieved over prior efforts for the interpolation step of a typical (255, 239) RS code, while the interpolation latency remains the same     

High-Speed Interpolation Architecture for Soft-Decision Decoding of Reed–Solomon Codes

Algebraic soft-decision decoding of Reed-Solomon (RS) codes delivers promising coding gains over conventional hard-decision decoding. The most computationally demanding step in soft-decision decoding of RS codes is bivariate polynomial interpolation. In this paper, we present a hybrid data format-based interpolation architecture that is well suited for high-speed implementation of the soft-decision decoders. It will be shown that this architecture is highly scalable and can be extensively pipelined. It also enables maximum overlap in time for computations at adjacent iterations. It is estimated that the proposed architecture can achieve significantly higher throughput than conventional designs with equivalent or lower hardware complexity     

Filterbank Decompositions for (Non)-Systematic Reed–Solomon Codes With Applications to Soft Decoding

This paper focuses on Reed-Solomon (RS) codes, which are the most widespread classical error correcting codes. Recently, we have shown that an finite-impulse response (FIR) critically subsampled filterbank representation can be derived for some RS codes. However, this work only addresses RS codes with a non-coprime codeword and dataword length, seriously limiting its practical usability. In this paper, an alternative purely algebraic method is presented to construct such a filterbank. Apart from providing additional insight into the algebraic structure of (non-systematic) RS codes, this method is suited to eliminate the non-coprimeness constraint mentioned before. Using this filterbank decomposition, a RS code is broken into smaller subcodes that can subsequently be used to build a soft-in soft-out (SISO) RS decoder. It is shown how any RS code, written as an FIR filterbank, can be SISO decoded using the filterbank based decoder. Owing to the importance of systematic RS codes, it is shown that any systematic RS code can be decoded using the FIR filterbank decomposition. This leads to better decoding performance in addition with a slightly lower complexity. A further extension towards systematic RS codes is also presented in this paper resulting in an infinite-impulse response critically subsampled filterbank representation.     

Low-Latency Factorization Architecture for Algebraic Soft-Decision Decoding of Reed–Solomon Codes

Bivariate polynomial factorization is an important stage of algebraic soft-decision decoding of Reed-Solomon (RS) codes and contributes to a significant portion of the overall decoding latency. With the exhaustive search-based root computation method, factorization latency is dominated by the root computation step, especially for RS codes defined over very large finite fields. The root-order prediction method proposed by Zhang and Parhi only improves average latency, but does not have any effect on the worst-case latency of the factorization procedure. Thus, neither approach is well-suited for delay-sensitive applications. In this paper, a novel architecture based on direct root computation is proposed to greatly reduce the factorization latency. Direct root computation is feasible because in most practical applications of algebraic soft-decision decoding of RS codes, enough decoding gain can be achieved with a relatively low interpolation cost, which results in a bivariate polynomial with low Y-degree. Compared with existing works, not only does the new architecture have a significantly smaller worst-case decoding latency, but it is also more area efficient since the corresponding hardware for routing polynomial coefficients is eliminated.     

How often is hard-decision decoding enough?

The problem of decoding binary linear block codes has received much attention; the two extremes are optimal, high-complexity soft-decision (or maximum-likelihood) decoding and lower performance, much lower complexity hard-decision (or algebraic) decoding. This article considers a class of decoders which first implements hard-decision decoding; second, tests to see if that is enough, that its result matches the result of soft-decision decoding; and third, continues to search if a match is not found. The advantage of such a testing procedure is that if the hard-decision decoding result is found to be enough (called a success for the test), then the computational effort expended by the decoder is low. The performance, as measured by the probability of a success, of a variety of simple tests of the hard-decision codeword are analyzed     

Construction of Quasi-Cyclic LDPC Codes for AWGN and Binary Erasure Channels: A Finite Field Approach

In the late 1950s and early 1960s, finite fields were successfully used to construct linear block codes, especially cyclic codes, with large minimum distances for hard-decision algebraic decoding, such as Bose-Chaudhuri-Hocquenghem (BCH) and Reed-Solomon (RS) codes. This paper shows that finite fields can also be successfully used to construct algebraic low-density parity-check (LDPC) codes for iterative soft-decision decoding. Methods of construction are presented. LDPC codes constructed by these methods are quasi-cyclic (QC) and they perform very well over the additive white Gaussian noise (AWGN), binary random, and burst erasure channels with iterative decoding in terms of bit-error probability, block-error probability, error-floor, and rate of decoding convergence, collectively. Particularly, they have low error floors. Since the codes are QC, they can be encoded using simple shift registers with linear complexity.     

Architecture and Implementation of an Interpolation Processor for Soft-Decision Reed–Solomon Decoding

Reed-Solomon codes are powerful error-correcting codes that can be found in many digital communications standards. Recently, there has been an interest in soft-decision decoding of Reed-Solomon codes, incorporating reliability information from the channel into the decoding process. The Koetter-Vardy algorithm is a soft-decision decoding algorithm for Reed-Solomon codes which can provide several dB of gain over traditional hard-decision decoders. The algorithm consists of a soft-decision front end to the interpolation-based Guruswami-Sudan list decoder. The main computational task in the algorithm is a weighted interpolation of a bivariate polynomial. We propose a parallel architecture for the hardware implementation of bivariate interpolation for soft-decision decoding. The key feature is the embedding of both a binary tree and a linear array into a 2-D array processor, enabling fast polynomial evaluation operations. An field-programmable gate array interpolation processor was implemented and demonstrated at a clock frequency of 23 MHz, corresponding to decoding rates of 10-15 Mb/s     

High rate concatenated coding systems using bandwidth efficienttrellis inner codes

High-rate concatenated coding systems with bandwidth-efficient trellis inner codes and Reed-Solomon (RS) outer codes are investigated for application in high-speed satellite communication systems. Two concatenated coding schemes are proposed. In one the inner code is decoded with soft-decision Viterbi decoding, and the outer RS code performs error-correction-only decoding (decoding without side information). In the other the inner code is decoded with a modified Viterbi algorithm, which produces reliability information along with the decoded output. In this algorithm, path metrics are used to estimate the entire information sequence, whereas branch metrics are used to provide reliability information on the decoded sequence. This information is used to erase unreliable bits in the decoded output. An errors-and-erasures RS decoder is then used for the outer code. The two schemes have been proposed for high-speed data communication on NASA satellite channels. The rates considered are at least double those used in current NASA systems, and the results indicate that high system reliability can still be achieved     

Computing upper bounds to error probability of soft-decision decoding of Reed-Solomon codes based on the ordered statistics algorithm

This correspondence presents performance analysis of symbol-level soft-decision decoding of q-ary maximum-distance-separable (MDS) codes based on the ordered statistics algorithm. The method we present is inspired by the one recently proposed by Agrawal and Vardy (2000), who approximately evaluate the performance of generalized minimum-distance decoding. The correspondence shows that in our context, the method allows us to compute the exact value of the probability that the transmitted codeword is not one of the candidate codewords. This leads to a close upper bound on the performance of the decoding algorithm. Application of the ordered statistics algorithm to MDS codes is not new. Nevertheless, its advantages seem not to be fully explored. We show an example where the decoding algorithm is applied to singly extended 16-ary Reed-Solomon (RS) codes in a 128-dimensional multilevel coded-modulation scheme that approaches the sphere lower bound within 0.5 dB at the word error probability of 10/sup -4/ with manageable decoding complexity.     

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.     

Fast factorization architecture in soft-decision Reed-Solomon decoding

Reed-Solomon (RS) codes are among the most widely utilized block error-correcting codes in modern communication and computer systems. Compared to its hard-decision counterpart, soft-decision decoding offers considerably higher error-correcting capability. The recent development of soft-decision RS decoding algorithms makes their hardware implementations feasible. Among these algorithms, the Koetter-Vardy (KV) algorithm can achieve substantial coding gain for high-rate RS codes, while maintaining a polynomial complexity with respect to the code length. In the KV algorithm, the factorization step can consume a major part of the decoding latency. A novel architecture based on root-order prediction is proposed in this paper to speed up the factorization step. As a result, the time-consuming exhaustive-search-based root computation in each iteration level, except the first one, of the factorization step is circumvented with more than 99% probability. Using the proposed architecture, a speedup of 141% can be achieved over prior efforts for a (255, 239) RS code, while the area consumption is reduced to 31.4%.     

Exponential error bounds for algebraic soft-decision decoding of Reed-Solomon codes

Algebraic soft-decision decoding of Reed-Solomon codes is a promising technique for exploiting reliability information in the decoding process. While the algorithmic aspects of the decoding algorithm are reasonably well understood and, in particular, complexity is polynomially bounded in the length of the code, the performance analysis has relied almost entirely on simulation results. Analytical exponential error bounds that can be used to tightly bound the performance of Reed-Solomon codes under algebraic soft-decision decoding are presented in this paper. The analysis is used in a number of examples and several extensions and consequences of the results are presented.