Low-density Parity-check Code Ensembles Research Articles

Finite-Length Scaling of SC-LDPC Codes With a Limited Number of Decoding Iterations

We propose four finite-length scaling laws to predict the frame error rate (FER) performance in the waterfall region of spatially-coupled low-density parity-check code ensembles under full belief propagation (BP) decoding with a limit on the number of decoding iterations and a scaling law for sliding window decoding, also with limited iterations. The laws for full BP decoding provide a choice between accuracy and computational complexity; a good balance between them is achieved by the law that models the number of decoded bits after a certain number of BP iterations by a time-integrated Ornstein-Uhlenbeck process. This framework is developed further to model sliding window decoding as a race between the integrated Ornstein-Uhlenbeck process and an absorbing barrier that corresponds to the left boundary of the sliding window. The proposed scaling laws yield accurate FER predictions for the semi-structured code ensembles proposed by Olmos and Urbanke.

Fully Absorbing Set Enumerators for Protograph-Based LDPC Code Ensembles

The average finite-length (elementary) fully absorbing set enumerators for binary protograph-based low-density parity-check (LDPC) code ensembles are derived. The method relies on generating functions, and it provides an efficient mean to obtain the normalized logarithmic asymptotic distribution of (elementary) fully absorbing sets. Using these results, the asymptotic distribution of (elementary) fully absorbing sets is evaluated for some protograph-based LDPC code ensembles. Numerical results show how the distributions can be used to estimate the error floor performance of protograph LDPC codes.

Rate-compatible multi-edge type low-density parity-check code ensembles for continuous-variable quantum key distribution systems

In this paper, we propose a design rule of rate-compatible punctured multi-edge type low-density parity-check (MET-LDPC) code ensembles with degree-one variable nodes for the information reconciliation (IR) of continuous-variable quantum key distribution (CV-QKD) systems. In addition to the rate compatibility, the design rule effectively resolves the high error-floor issue which has been known as a technical challenge of MET-LDPC codes at low rates. Thus, the proposed design rule allows one to implement rate-compatible MET-LDPC codes with good performances both in the threshold and low-error-rate regions. The rate compatibility and the improved error-rate performances significantly enhance the efficiency of IR for CV-QKD systems. The performance improvements are confirmed by comparing complexities and secret key rates of IR schemes with MET-LDPC codes whose ensembles are optimized with the proposed and existing design rules. In particular, the SNR range of positive secrecy rate increases by 1.44 times, and the maximum secret key rate improves by 2.10 times as compared to the existing design rules. The comparisons clearly show that an IR scheme can achieve drastic performance improvements in terms of both the complexity and secret key rate by employing rate-compatible MET-LDPC codes constructed with code ensembles optimized with the proposed design rule.

The Stability of Low-Density Parity-Check Codes and Some of its Consequences

We study the stability of low-density parity-check codes under blockwise or bitwise maximum a posteriori decoding, where transmission takes place over a binary-input memoryless output-symmetric channel. Our study stems from the consideration of constructing universal capacity-achieving codes under low-complexity decoding algorithms, where universality refers to the fact that we are considering a family of channels with equal capacity. Consider, e.g., the right-regular sequence by Shokrollahi and the heavy-tail Poisson sequence by Luby et al. Both sequences are provably capacity-achieving under belief propagation decoding when transmission takes place over the binary erasure channel. In this paper we show that many existing capacity-achieving sequences of low-density parity-check codes are not universal under belief propagation decoding. We reveal that the key to showing this non-universality result is determined by the stability of the underlying codes. More concretely, for an ordered and complete channel family and a sequence of low-density parity-check code ensembles, we determine a stability threshold associated with them, which gives rise to a sufficient condition under which the sequence is not universal under belief propagation decoding. Moreover, we show that the same stability threshold applies to blockwise or bitwise maximum a posteriori decoding as well. We demonstrate how the stability threshold can determine an upper bound on the corresponding blockwise or bitwise maximum a posteriori threshold, revealing the operational significance of the stability threshold.

Spatially coupled turbo-coded continuous phase modulation: asymptotic analysis and optimization

For serially or parallel concatenated communication systems, spatial coupling techniques enable to improve the threshold of these systems under iterative decoding using belief propagation (BP). For the case of low-density parity-check (LDPC) codes, it has been shown that, under some asymptotic assumptions, spatially coupled ensembles have BP thresholds that approach the bitwise maximum a posteriori (MAP) threshold of the related uncoupled ensemble. This phenomenon is often referred to as threshold saturation, and it has sometimes very important consequences. For example, in the case of regular LDPC code ensembles, spatial coupling enables to achieve asymptotically the capacity for any class of binary memoryless symmetric channels. Since then, this threshold saturation has been conjectured or proved for several other types of concatenations. In this work, we consider a serially concatenated scheme which is the serial concatenation of a simple outer convolutional code and a continuous phase modulator (CPM) separated by an interleaver. Then, we propose a method to do the spatial coupling of several replicas of this serially concatenated scheme, aiming to improve the asymptotic convergence threshold. First, exploiting the specific structure of the proposed system, an original procedure is proposed in order to terminate the spatially coupled turbo-coded CPM scheme. In particular, the proposed procedure aims to ensure the continuity of the transmitted signal among spatially coupled replicas, enabling to keep one of the core characteristics and advantages of coded CPM schemes. Then, based on an asymptotic analysis, we show that the proposed scheme has very competitive thresholds when compared to carefully designed spatially coupled LDPC codes. Furthermore, it is shown how we can accelerate the convergence rate of the designed systems by optimizing the connection distributions in the coupling matrices. Finally, by investigating on different continuous phase modulation schemes, we corroborate the conjecture stating that spatially coupled turbo-coded CPM schemes saturate to a lower bound very close to the threshold given by the extrinsic information transfer (EXIT) area theorem.

Asymptotic Average Multiplicity of Structures Within Different Categories of Trapping Sets, Absorbing Sets, and Stopping Sets in Random Regular and Irregular LDPC Code Ensembles

The performance of low-density parity-check (LDPC) codes in the error floor region is closely related to some substructures of the code's Tanner graph, collectively referred to as trapping sets (TSs). In this paper, we study the asymptotic average number of different types of trapping sets such as elementary TSs (ETS), leafless ETSs (LETS), absorbing sets (ABS), elementary ABSs (EABS), and stopping sets (SS), in random variable-regular and irregular LDPC code ensembles. We demonstrate that, regardless of the type of the TS, as the code's length tends to infinity, the average number of a given structure tends to infinity, to a positive constant, or to zero, if the structure contains no cycle, only one cycle, or more than one cycle, respectively. For the case where the structure contains a single cycle, we derive the asymptotic expected multiplicity of the structure by counting the average number of its constituent cycles and all the possible ways that the structure can be constructed from the cycle. This, in general, involves computing the expected number of cycles of a certain length with a certain given combination of node degrees, or computing the expected number of cycles of a certain length expanded to the desired structure by the connection of trees to its nodes. The asymptotic results obtained in this work, which are independent of the block length and only depend on the code's degree distributions, are shown to be accurate even for finite-length codes.

LDPC Code Design for Fading Interference Channels

We focus on the two-user Gaussian interference channel (IC) with fading and study implementation of different encoding/decoding schemes with low-density parity-check (LDPC) codes for both quasi-static and fast fading scenarios. We adopt Han–Kobayashi encoding, derive stability conditions on the degree distributions of LDPC code ensembles, and obtain explicit and practical code designs. In order to estimate the decoding thresholds, a modified form of the extrinsic information transfer chart analysis based on binary erasure channel approximation for the incoming messages from the component LDPC decoders to state nodes is developed. The proposed code design is employed in several examples for both fast and quasi-static fading cases. Comprehensive set of examples demonstrate that the designed codes perform close to the achievable information theoretic limits. Furthermore, multiple antenna transmissions employing the Alamouti scheme for fading ICs are studied, a special receiver structure is developed, and specific codes are explored. Finally, advantages of the designed codes over point-to-point optimal ones are demonstrated via both asymptotic and finite block length simulations.

On the Tanner Graph Cycle Distribution of Random LDPC, Random Protograph-Based LDPC, and Random Quasi-Cyclic LDPC Code Ensembles

In this paper, we study the cycle distribution of random low-density parity-check (LDPC) codes, randomly constructed protograph-based LDPC codes, and random quasi-cyclic (QC) LDPC codes. We prove that for a random bipartite graph, with a given (irregular) degree distribution, the distributions of cycles of different length tend to independent Poisson distributions, as the size of the graph tends to infinity. We derive asymptotic upper and lower bounds on the expected values of the Poisson distributions that are independent of the size of the graph, and only depend on the degree distribution and the cycle length. For a random lift of a bi-regular protograph, we prove that the asymptotic cycle distributions are essentially the same as those of random bipartite graphs as long as the degree distributions are identical. For random QC-LDPC codes, however, we show that the cycle distribution can be quite different from the other two categories. In particular, depending on the protograph and the value of $c$ , the expected number of cycles of length $c$ , in this case, can be either $\Theta (N)$ or $\Theta (1)$ , where $N$ is the lifting degree (code length). We also provide numerical results that match our theoretical derivations. Our results provide a theoretical foundation for emperical results that were reported in the literature but were not well-justified. They can also be used for the analysis and design of LDPC codes and associated algorithms that are based on cycles.

Weight Distributions of Non-Binary Multi-Edge Type LDPC Code Ensembles: Analysis and Efficient Evaluation

Non-binary multi-edge type ensembles of low-density parity-check codes are analyzed in terms of non-binary codeword weight distribution and its growth rate. In particular, an exact expression of the growth rate for small weights is developed. As a side result, the stopping set distributions of these ensembles are developed. Examples of weight distributions are provided, showing that the derived closed-form expressions can be easily evaluated. The obtained results can thus be exploited to analyze and design non-binary low-density parity-check codes that fall within the multi-edge type framework such as, but not limited to, protograph-based codes.

EXIT Chart Aided LDPC Code Design for Symmetric Alpha-Stable Impulsive Noise

In this letter, an iterative analysis method based on an extrinsic information transfer (EXIT) chart and quantized density evolution is developed for low-density parity-check (LDPC) codes over channels with symmetric alpha-stable ( $\text{S}\alpha \text{S}$ ) impulsive noise. Based on the proposed scheme, a method to optimize ensembles of LDPC codes under different levels of impulsiveness is presented and it is shown that the information rates of our optimized code ensembles can achieve 95.4% and 94.7% of the channel capacity for $\alpha =1.8$ and $\alpha =1$ , respectively. Furthermore, experimental results, including EXIT curves, thresholds, and bit-error rate performance of optimized code ensembles, are obtained to verify the effectiveness of our analysis.

Distance Verification for Classical and Quantum LDPC Codes

The techniques of distance verification known for general linear codes are first applied to the quantum stabilizer codes. Then, these techniques are considered for classical and quantum (stabilizer) low-density-parity-check (LDPC) codes. New complexity bounds for distance verification with provable performance are derived using the average weight spectra of the ensembles of LDPC codes. These bounds are expressed in terms of the erasure-correcting capacity of the corresponding ensemble. We also present a new irreducible-cluster technique that can be applied to any LDPC code and takes advantage of parity-checks’ sparsity for both the classical and quantum LDPC codes. This technique reduces complexity exponents of all existing deterministic techniques designed for generic stabilizer codes with small relative distances, which also include all known families of the quantum stabilizer LDPC codes.

Analysis of Saturated Belief Propagation Decoding of Low-Density Parity-Check Codes

We consider the effect of log-likelihood ratio saturation on the belief-propagation decoding of low-density parity-check codes. Saturation is commonly done in practice and is known to have a significant effect on the error-floor performance. Our focus is on threshold analysis and the stability of density evolution. We analyze the decoder for standard low-density parity-check code ensembles and show that belief-propagation decoding generally degrades gracefully with saturation. Stability of density evolution is, on the other hand, rather strongly affected by saturation, and the asymptotic qualitative effect of saturation is similar to reduction by one of variable-node degree. We also describe conditions under which the block-error threshold for saturated belief-propagation decoding equals the bit-error threshold.

Rate‐compatible spatially coupled LDPC code ensembles based on repeat‐accumulate extensions

A family of rate-compatible capacity-approaching codes is obtained by spatially coupling multiple identical copies of rate-compatible base codes. The base code consists of a given regular low-density parity-check (LDPC) code and a parameter-adjustable repeat-accumulate (RA) extension. The RA-extension repeatedly accumulates all of the variable nodes of the given LDPC code by q + 1 times to generate q + 1 blocks of accumulated nodes, in which all of the accumulated variable nodes in the first q blocks and the α-fractional accumulated variable nodes in the last block are transmitted. The spatially coupled versions of the base codes, called RA-extended spatially coupled LDPC (SC-LDPC) codes, achieve arbitrary rates by simply adjusting parameters q and α, and thus they are rate-compatible. The potential thresholds of the base code ensembles are calculated to predict the iterative decoding performance of the proposed RA-extended SC-LDPC codes. Numerical results and simulations show that the authors’ proposed rate-compatible codes are capacity-approaching over binary erasure channels.

Efficient and Exact Evaluation of the Weight Spectral Shape and Typical Minimum Distance of Protograph LDPC Codes

In this letter, an analytical method for evaluating the weight spectral shape of a nonbinary protograph low-density parity-check code ensemble is provided. This method, which requires simultaneous solution of a system of equations, is more efficient to implement than the existing methods that require the numerical solution of a high-dimensional maximization problem. It is also shown that by adding a single equation to the proposed system, it is possible to directly solve for the typical minimum distance of the ensemble. This makes the proposed method particularly useful for the ensemble design scenario where a constraint is placed on the typical minimum distance. The proposed method is verified through the evaluation of the weight spectral shape of some example protograph ensembles.

LDPC Code Design for the Two-User Gaussian Multiple Access Channel

We study code design for two-user Gaussian multiple access channels (GMACs) under fixed channel gains and under quasi-static fading. We employ low-density parity-check (LDPC) codes with BPSK modulation and utilize an iterative joint decoder. Adopting a belief propagation (BP) algorithm, we derive the PDF of the log-likelihood-ratios (LLRs) fed to the component LDPC decoders. Via examples, it is illustrated that the characterized PDF resembles a Gaussian mixture (GM) distribution, which is exploited in predicting the decoding performance of LDPC codes over GMACs. Based on the GM assumption, we propose variants of existing analysis methods, named modified density evolution (DE) and modified extrinsic information transfer (EXIT). We derive a stability condition on the degree distributions of the LDPC code ensembles and utilize it in the code optimization. Under fixed channel gains, the newly optimized codes are shown to perform close to the capacity region boundary outperforming the existing designs and the off-the-shelf point-to-point (P2P) codes. Under quasi-static fading, optimized codes exhibit consistent improvements upon the P2P codes as well. Finite block length simulations of specific codes picked from the designed ensembles are also carried out and it is shown that optimized codes perform close to the outage limits.

Randomly Punctured LDPC Codes

In this paper, we present a random puncturing analysis of low-density parity-check (LDPC) code ensembles. We derive a simple analytic expression for the iterative belief propagation (BP) decoding threshold of a randomly punctured LDPC code ensemble on the binary erasure channel (BEC) and show that, with respect to the BP threshold, the strength and suitability of an LDPC code ensemble for random puncturing is completely determined by a single constant that depends only on the rate and the BP threshold of the mother code ensemble. We then provide an efficient way to accurately predict BP thresholds of randomly punctured LDPC code ensembles on the binary-input additive white Gaussian noise channel (BI-AWGNC), given only the BP threshold of the mother code ensemble on the BEC and the design rate, and we show how the prediction can be improved with knowledge of the BI-AWGNC threshold. We also perform an asymptotic minimum distance analysis of randomly punctured code ensembles and present simulation results that confirm the robust decoding performance promised by the asymptotic results. Protograph-based LDPC block code and spatially coupled LDPC code ensembles are used throughout as examples to demonstrate the results.

Asymptotic bounds on the decoding error probability for two ensembles of LDPC codes

Two ensembles of low-density parity-check (LDPC) codes with low-complexity decoding algorithms are considered. The first ensemble consists of generalized LDPC codes, and the second consists of concatenated codes with an outer LDPC code. Error exponent lower bounds for these ensembles under the corresponding low-complexity decoding algorithms are compared. A modification of the decoding algorithm of a generalized LDPC code with a special construction is proposed. The error exponent lower bound for the modified decoding algorithm is obtained. Finally, numerical results for the considered error exponent lower bounds are presented and analyzed.

Design of LDPC Codes for Two-Way Relay Systems with Physical-Layer Network Coding

This letter presents low-density parity-check (LDPC) code design for two-way relay (TWR) systems employing physical-layer network coding (PLNC). We focus on relay decoding, and propose an empirical density evolution method for estimating the decoding threshold of the LDPC code ensemble. We utilize the proposed method in conjunction with a random walk optimization procedure to obtain good LDPC code degree distributions. Numerical results demonstrate that the specifically designed LDPC codes can attain improvements of about 0.3 dB over off-the-shelf LDPC codes (designed for point-to-point additive white Gaussian noise channels), i.e., it is new code designs are essential to optimize the performance of TWR systems.

Weight Distribution for Non-binary Cluster LDPC Code Ensemble

In this paper, we derive the average weight distributions for the irregular non-binary cluster low-density parity-check (LDPC) code ensembles. Moreover, we give the exponential growth rate of the average weight distribution in the limit of large code length. We show that there exist $(2,d_c)$-regular non-binary cluster LDPC code ensembles whose normalized typical minimum distances are strictly positive.

Iterative Linear Programming Decoding of Nonbinary LDPC Codes With Linear Complexity

The problem of low-complexity linear programming (LP) decoding of nonbinary low-density parity-check (LDPC) codes is considered, and an iterative LP decoding algorithm is presented. Results that were previously derived for binary LDPC codes are extended to the nonbinary case. Both simple and generalized nonbinary LDPC codes are considered. It is shown how the algorithm can be implemented efficiently using a finite-field fast Fourier transform. Then, the convergence rate of the algorithm is analyzed. The complexity of the algorithm scales linearly in the block length, and it can approximate, up to an arbitrarily small relative error, the objective function of the exact LP solution. When applied to a typical code from an appropriate nonbinary LDPC code ensemble, the algorithm can correct a constant fraction of errors in linear (in the block length) computational complexity. Computer experiments with the new iterative LP decoding algorithm show that, in the error floor region, it can have better performance compared to belief propagation decoding, with similar computational requirements.