Correcting capabilities of binary irregular LDPC code under low-complexity iterative decoding algorithm

This paper deals with the irregular binary low-density parity-check (LDPC) codes and two iterative low-complexity decoding algorithms. The first one is the majority error-correcting decoding algorithm, and the second one is iterative erasure-correcting decoding algorithm. The lower bounds on correcting capabilities (the guaranteed corrected error and erasure fraction respectively) of irregular LDPC code under decoding (error and erasure correcting respectively) algorithms with low-complexity were represented. These lower bounds were obtained as a result of analysis of Tanner graph representation of irregular LDPC code. The numerical results, obtained at the end of the paper for proposed lower-bounds achieved similar results for the previously known best lower-bounds for regular LDPC codes and were represented for the first time for the irregular LDPC codes.     

Joint iterative decoding for pragmatic irregular LDPC-coded multi-relay cooperations

In this article, a new kind of pragmatic simple-encoding irregular systematic low-density parity-check (LDPC) code for multi-relay coded cooperation is designed, where the introduced joint iterative decoding is performed in the destination based on a proposed joint Tanner graph for all the constituent LDPC codes used by the source and relays in multi-relay cooperation. The theoretical analysis and numerical results show that the coded cooperations outperform the coded non-cooperation under the same code rate, and also achieve a good trade-off between the performance and the decoding complexity associated with the number of relays. This performance gain can be credited to the additional exchange of extrinsic information from the LDPC codes used by the source and the relays in both ideal and non-ideal cooperations.     

Single-block coded modulation for MINO systems

This paper introduces a new class of space-time codes that achieve coding gain without a trellis or any form of inter-block dependency. The construction of the new codes starts from an existing (parent) space-time block code (STBC). Then by increasing the constellation size followed by expurgation of the expanded codebook, a better code is obtained at the original transmission rate. This method can be applied to a wide variety of space-time block codes, including orthogonal codes and quasi-orthogonal codes. A multi-stage design algorithm is presented, and for orthogonal parent codes, an efficient decoding algorithm is developed, and its decoding complexity is analyzed. Despite altering the regular structure of the orthogonal code, the decoding complexity is only affected by a constant factor.     

Closest coset decoding of |u|u+v| codes

The general concept of closest coset decoding (CCD) is presented, and a soft-decoding technique for block codes that is based on partitioning a code into a subcode and its cosets is described. The computational complexity of the CCD algorithm is significantly less than that required if a maximum-likelihood detector (MLD) is used. A set-partitioning procedure and details of the CCD algorithm for soft decoding of |u|u+v| codes are presented. Upper bounds on the bit-error-rate (BER) performance of the proposed algorithm are combined, and numerical results and computer simulation tests for the BER performance of second-order Reed-Muller codes of length 16 and 32 are presented. The algorithm is a suboptimum decoding scheme and, in the range of signal-to-noise-power-density ratios of interest, its BER performance is only a few tenths of a dB inferior to the performance of the MLD for the codes examined     

High-performance simple-encoding generator-based systematic irregular LDPC codes and resulted product codes

Low-Density Parity-Check (LDPC) code is one of the most exciting topics among the coding theory community.It is of great importance in both theory and practical communications over noisy channels.The most advantage of LDPC codes is their relatively lower decoding complexity compared with turbo codes,while the disadvantage is its higher encoding complexity.In this paper,a new ap- proach is first proposed to construct high performance irregular systematic LDPC codes based on sparse generator matrix,which can significantly reduce the encoding complexity under the same de- coding complexity as that of regular or irregular LDPC codes defined by traditional sparse parity-check matrix.Then,the proposed generator-based systematic irregular LDPC codes are adopted as con- stituent block codes in rows and columns to design a new kind of product codes family,which also can be interpreted as irregular LDPC codes characterized by graph and thus decoded iteratively.Finally, the performance of the generator-based LDPC codes and the resultant product codes is investigated over an Additive White Gaussian Noise (AWGN) and also compared with the conventional LDPC codes under the same conditions of decoding complexity and channel noise.     

Degree-Matched Check Node Decoding for Regular and Irregular LDPCs

This brief examines different parity-check node decoding algorithms for low-density parity-check (LDPC) codes, seeking to recoup the performance loss incurred by the min-sum approximation compared to sum-product decoding. Two degree-matched check node decoding approximations that depend on the check node degree d_c are presented. Both have low complexity and can be applied to any degree distribution. Simulation results show near sum-product decoding performance for both degree-matched check node approximations for regular and irregular LDPCs     

Suboptimum decoding of decomposable block codes

To decode a long block code with a large minimum distance by maximum likelihood decoding is practically impossible because the decoding complexity is simply enormous. However, if a code can be decomposed into constituent codes with smaller dimensions and simpler structure, it is possible to devise a practical and yet efficient scheme to decode the code. This paper investigates a class of decomposable codes, their distance and structural properties. It is shown that this class includes several classes of well-known and efficient codes as subclasses. Several methods for constructing decomposable codes or decomposing codes are presented. A two-stage (soft-decision or hard-decision) decoding scheme for decomposable codes, their translates or unions of translates is devised, and its error performance is analyzed for an AWGN channel. The two-stage soft-decision decoding is suboptimum. Error performances of some specific decomposable codes based on the proposed two-stage soft-decision decoding are evaluated. It is shown that the proposed two-stage suboptimum decoding scheme provides an excellent trade-off between the error performance and decoding complexity for codes of moderate and long block length     

Novel modified min-sum decoding algorithm for low-density parity-check codes

The problem of improving the performance of min-sum decoding of low-density parity-check(LDPC)codes is considered in this paper.Based on rain-sum algorithm,a novel modified min-sum decoding algorithm for LDPC codes is proposed.The proposed algorithm modifies the variable node message in the iteration process by averaging the new message and previous message if their signs are different.Compared with the standard min-sum algorithm,the modification is achieved with only a small increase in complexity,but significantly improves decoding performance for both regular and irregular LDPC codes.Simulation results show that the performance of our modified decoding algorithm is very close to that of the standard sum-produet algorithm for moderate length LDPC codes.     

Gaussian integers and interleaved rank codes for space–time block codes

This paper presents the design of space–time block codes (STBCs) over maximum rank distance (MRD) codes, energy‐efficient STBCs, STBCs using interleaved‐MRD codes, the use of Gaussian integers for STBCs modulation, and Gabidulin's decoding algorithm for decoding STBCs. The design fundamentals of STBCs using MRD codes are firstly put forward for different number of transmit antennas. Extension finite fields (Galois fields) are used to design these linear block codes. Afterward, a comparative study of MRD‐based STBCs with corresponding orthogonal and quasi‐orthogonal codes is also included in the paper. The simulation results show that rank codes, for any number of transmit antennas, exhibit diversity gain at full rate contrary to orthogonal codes, which give diversity gain at full rate only for two transmit antennas case. Secondly, an energy‐efficient MRD‐STBC is proposed, which outperforms orthogonal STBC at least for 2 × 1 antenna system. Thirdly, interleaved‐MRD codes are used to construct higher‐order transmit antenna systems. Using interleaved‐MRD codes further reduces the complexity (compared with normal MRD codes) of the decoding algorithm. Fourthly, the use of Gaussian integers is utilized in mapping MRD‐based STBCs to complex constellations. Furthermore, it is described how an efficient and computationally less complex Gabidulin's decoding algorithm can be exploited for decoding complex MRD‐STBCs. The decoding results have been compared against hard‐decision maximum likelihood decoding. Under this decoding scheme, MRD‐STBCs have been shown to be potential candidate for higher transmit antenna systems as the decoding complexity of Gabidulin's algorithm is far less, and its performance for decoding MRD‐STBCs is somewhat reasonable. Copyright © 2015 John Wiley & Sons, Ltd.     

Performance analysis and code optimization of low densityparity-check codes on Rayleigh fading channels

A numerical method has been presented to determine the noise thresholds of low density parity-check (LDPC) codes that employ the message passing decoding algorithm on the additive white Gaussian noise (AWGN) channel. In this paper, we apply the technique to the uncorrelated flat Rayleigh fading channel. Using a nonlinear code optimization technique, we optimize irregular LDPC codes for such a channel. The thresholds of the optimized irregular LDPC codes are very close to the Shannon limit for this channel. For example, at rate one-half, the optimized irregular LDPC code has a threshold only 0.07 dB away from the capacity of the channel. Furthermore, we compare simulated performance of the optimized irregular LDPC codes and turbo codes on a land mobile channel, and the results indicate that at a block size of 3072, irregular LDPC codes can outperform turbo codes over a wide range of mobile speeds     

An efficient decoding algorithm for block turbo codes

An efficient soft-input soft-output iterative decoding algorithm for block turbo codes (BTCs) is proposed. The proposed algorithm utilizes Kaneko's (1994) decoding algorithm for soft-input hard-output decoding. These hard outputs are converted to soft-decisions using reliability calculations. Three different schemes for reliability calculations incorporating different levels of approximation are suggested. The algorithm proposed here presents a major advantage over existing decoding algorithms for BTCs by providing ample flexibility in terms of performance-complexity tradeoff. This makes the algorithm well suited for wireless multimedia applications. The algorithm can be used for optimal as well as suboptimal decoding. The suboptimal versions of the algorithm can be developed by changing a single parameter (the number of error patterns to be generated). For any performance, the computational complexity of the proposed algorithm is less than the computational complexity of similar existing algorithms. Simulation results for the decoding algorithm for different two-dimensional BTCs over an additive white Gaussian noise channel are shown. A performance comparison of the proposed algorithm with similar existing algorithms is also presented     

基于节点子集和k阶信息截断的多元LDPC译码算法

本文提出一种低复杂度的多元LDPC译码算法,从以下两个方面降低复杂度：（1）提出一种节点截断策略,构造处理/非处理校验节点子集,使得一部分足够可靠的校验节点不进行信息更新,从而减少运算量;（2）针对处理校验节点子集,本文进而提出一种k阶信息截断准则,对Trellis图上的边和状态进行划分.在迭代递归过程中,只有"活"的状态/边才参与运算,可进一步降低校验节点的计算量.仿真表明,本文算法的译码性能与现有的几种EMS改进算法非常接近;在译码复杂度方面,不管对高阶域还是低阶域的多元LDPC码,本文算法的复杂度都是最小的.     

Guessing Facets: Polytope Structure and Improved LP Decoder

We investigate the structure of the polytope underlying the linear programming (LP) decoder introduced by Feldman, Karger, and Wainwright. We first show that for expander codes, every fractional pseudocodeword always has at least a constant fraction of nonintegral bits. We then prove that for expander codes, the active set of any fractional pseudocodeword is smaller by a constant fraction than that of any codeword. We further exploit these geometrical properties to devise an improved decoding algorithm with the same order of complexity as LP decoding that provably performs better. The method is very simple: it first applies ordinary LP decoding, and when it fails, it proceeds by guessing facets of the polytope, and then resolving the linear program on these facets. While the LP decoder succeeds only if the ML codeword has the highest likelihood over all pseudocodewords, we prove that the proposed algorithm, when applied to suitable expander codes, succeeds unless there exists a certain number of pseudocodewords, all adjacent to the ML codeword on the LP decoding polytope, and with higher likelihood than the ML codeword. We then describe an extended algorithm, still with polynomial complexity, that succeeds as long as there are at most polynomially many pseudocodewords above the ML codeword.     

The Minimum Decoding Delay of Maximum Rate Complex Orthogonal Space–Time Block Codes

The growing demand for efficient wireless transmissions over fading channels motivated the development of space-time block codes. Space-time block codes built from generalized complex orthogonal designs are particularly attractive because the orthogonality permits a simple decoupled maximum-likelihood decoding algorithm while achieving full transmit diversity. The two main research problems for these complex orthogonal space-time block codes (COSTBCs) have been to determine for any number of antennas the maximum rate and the minimum decoding delay for a maximum rate code. The maximum rate for COSTBCs was determined by Liang in 2003. This paper addresses the second fundamental problem by providing a tight lower bound on the decoding delay for maximum rate codes. It is shown that for a maximum rate COSTBC for 2m - 1 or 2m antennas, a tight lower bound on decoding delay is r = (_m-1 ^2m) . This lower bound on decoding delay is achievable when the number of antennas is congruent to 0, 1, or 3 modulo 4. This paper also derives a tight lower bound on the number of variables required to construct a maximum rate COSTBC for any given number of antennas. Furthermore, it is shown that if a maximum rate COSTBC has a decoding delay of r where r < r les 2r, then r=2r. This is used to provide evidence that when the number of antennas is congruent to 2 modulo 4, the best achievable decoding delay is 2(_m-1 ^2m_).     

Shuffled iterative decoding

Shuffled versions of iterative decoding of low-density parity-check codes and turbo codes are presented. The proposed schemes have about the same computational complexity as the standard versions, and converge faster. Simulations show that the new schedules offer better performance/complexity tradeoffs, especially when the maximum number of iterations has to remain small.     

基于循环检测的LDPC比特翻转译码算法研究

提出一种基于循环检测的低密度奇偶校验码的比特翻转(BF)译码算法,采用对译码翻转比特的循环检测和对接受符号可靠性信息的软判决,使译码性能大大改善.理论分析表明,该译码运算复杂度低,仿真结果表明,改进的算法优于加权比特翻转译码LP-WBF算法约0.3 dB,误码性能改善明显.     

A trellis-based recursive maximum-likelihood decoding algorithm forbinary linear block codes

This paper presents an efficient trellis-based maximum-likelihood decoding algorithm for binary linear block codes. This algorithm is recursive in nature and is devised based on the structural properties and optimum sectionalization of a code trellis. The complexity of the proposed decoding algorithm is analyzed. Numerical results show that the proposed decoding algorithm significantly reduces the decoding complexity. A recursive method for finding the optimum sectionalization of a trellis in terms of computational complexity is given     

Error rate estimation of low-density parity-check codes on binary symmetric channels using cycle enumeration

The performance of low-density parity-check (LDPC) codes decoded by hard-decision iterative decoding algorithms can be accurately estimated if the weight J and the number |E_J| of the smallest error patterns that cannot be corrected by the decoder are known. To obtain J and |E_J|, one would need to perform the direct enumeration of error patterns with weight ι ⩽ J. The complexity of enumeration increases exponentially with J, essentially as η^J, where η is the code block length. This limits the application of direct enumeration to codes with small η and J. In this letter, we approximate J and |E_J | by enumerating and testing the error patterns that are subsets of short cycles in the code's Tanner graph. This reduces the computational complexity by several orders of magnitude compared to direct enumeration, making it possible to estimate the error rates for almost any practical LDPC code. To obtain the error rate estimates, we propose an algorithm that progressively improves the estimates as larger cycles are enumerated. Through a number of examples, we demonstrate that the proposed method can accurately estimate both the bit error rate (BER) and the frame error rate (FER) of regular and irregular LDPC codes decoded by a variety of hard-decision iterative decoding algorithms.     

Decoding with Early Termination for Raptor Codes

Rateless codes, and especially Raptor codes, have received considerable attention in the recent past due to their inherent ability to adapt to channel conditions and their capacity- approaching performance. Since decoding of rateless codes typically involves multiple decoding attempts, early termination of such attempts is mandatory for overall efficient decoding. In this letter, we propose a new decoding scheme with early termination that is particularly suited for rateless codes. Simulation results for the example of the binary symmetric channel show complexity reductions (in terms of the total required number of decoding iterations) by 87% compared to conventional message-passing decoding and 54% compared to a recently proposed incremental decoding scheme for Raptor codes.     

Iterative reliability-based decoding of low-density parity checkcodes

In this paper, reliability based decoding is combined with belief propagation (BP) decoding for low-density parity check (LDPC) codes. At each iteration, the soft output values delivered by the BP algorithm are used as reliability values to perform reduced complexity soft decision decoding of the code considered. This approach allows to bridge the error performance gap between belief propagation decoding which remains suboptimum, and maximum likelihood decoding which is too complex to be implemented for the codes considered. Trade-offs between decoding complexity and error performance are also investigated. In particular, a stopping criterion which reduces the average number of iterations at the expense of very little performance degradation is proposed for this combined decoding approach. Simulation results for several Gallager (1963, 1968) LDPC codes and different set cyclic codes of hundreds of information bits are given and elaborated