Class Of Low-density Parity-check Codes Research Articles

Partitioning qubits in hypergraph product codes to implement logical gates

The promise of high-rate low-density parity check (LDPC) codes to substantially reduce the overhead of fault-tolerant quantum computation depends on constructing efficient, fault-tolerant implementations of logical gates on such codes. Transversal gates are the simplest type of fault-tolerant gate, but the potential of transversal gates on LDPC codes has hitherto been largely neglected. We investigate the transversal gates that can be implemented in hypergraph product codes, a class of LDPC codes. Our analysis is aided by the construction of a symplectic canonical basis for the logical operators of hypergraph product codes, a result that may be of independent interest. We show that in these codes transversal gates can implement Hadamard (up to logical SWAP gates) and control-Z on all logical qubits. Moreover, we show that sequences of transversal operations, interleaved with error correction, allow implementation of entangling gates between arbitrary pairs of logical qubits in the same code block. We thereby demonstrate that transversal gates can be used as the basis for universal quantum computing on LDPC codes, when supplemented with state injection.

Алгоритмы итеративного приёма кодов-произведений на основе низкоплотностных кодов проективной геометрии

The focus of this paper is directed towards the investigation of the characteristics of symbol-by-symbol iterative decoding algorithms for error-correcting block product-codes (block turbo-codes) which enable to reliable information transfer at relatively low received signal/noise and provide high power efficiency. Specific feature of investigated product codes is construction with usage of low-density parity-check codes (LDPC) and these code constructions are in the class of LDPC too. According to this fact the considered code constructions have symbol-by-symbol decoding algorithms developed for total class LDPC codes, namely BP (belief propagation) and its modification MIN_SUM_BP. The BP decoding algorithm is iterative and for implementation the signal/noise is required, for implementation of MIN_SUM_BP decoding algorithm the signal/noise is not required. The resulted characteristics of product codes constructed with usage of LDPC based on project geometry (length of code words, information volume, code rate, error performances) are presented in this paper. These component LDPC codes are cyclic and have encoding and decoding algorithms with low complexity implementation. The computer simulations for encoding and iterative symbol-by-symbol decoding algorithms for the number of turbo-codes with different code rate and information volumes are performed. The results of computer simulations have shown that MIN_SUM_BP decoding algorithm is more effective than BP decoding algorithm for channel with additive white gaussian noise concerning error-performances.

A Threshold-Based Min-Sum Algorithm to Lower the Error Floors of Quantized LDPC Decoders

For decoding low-density parity-check (LDPC) codes, the attenuated min-sum algorithm (AMSA) and the offset min-sum algorithm (OMSA) can outperform the conventional min-sum algorithm (MSA) at low signal-to-noise-ratios (SNRs), i.e., in the “waterfall region” of the bit error rate curve. This paper demonstrates that, for quantized decoders, MSA actually outperforms AMSA and OMSA in the “error floor” region, and that all three algorithms suffer from a relatively high error floor. This motivates the introduction of a modified MSA that is designed to outperform MSA, AMSA, and OMSA across all SNRs. The new algorithm is based on the assumption that trapping sets are the major cause of the error floor for quantized LDPC decoders. A performance estimation tool based on trapping sets is used to verify the effectiveness of the new algorithm and also to guide parameter selection. We also show that the implementation complexity of the new algorithm is only slightly higher than that of AMSA or OMSA. Finally, the simulated performance of the new algorithm, using several classes of LDPC codes (including spatially coupled LDPC codes), is shown to outperform MSA, AMSA, and OMSA across all SNRs.

Performance Bounds and Estimates for Quantized LDPC Decoders

The performance of low-density parity-check (LDPC) codes at high signal-to-noise ratios (SNRs) is known to be limited by the presence of certain sub-graphs that exist in the Tanner graph representation of the code, for example trapping sets and absorbing sets. This paper derives a lower bound on the frame error rate (FER) of any LDPC code containing a given problematic sub-graph, assuming a particular message passing decoder and decoder quantization. A crucial aspect of the lower bound is that it is code-independent, in the sense that it can be derived based only on a problematic sub-graph and then applied to any code containing it. Due to the complexity of evaluating the exact bound, assumptions are proposed to approximate it, from which we can estimate decoder performance. Simulated results obtained for both the quantized sum-product algorithm (SPA) and the quantized min-sum algorithm (MSA) are shown to be consistent with the approximate bound and the corresponding performance estimates. Different classes of LDPC codes, including both structured and randomly constructed codes, are used to demonstrate the robustness of the approach.

Anti Quasi-Cyclic LDPC Codes

Low-density parity-check (LDPC) codes based on affine permutation matrices, APM-LDPC codes, have been attracted recently, because of some advantages rather than QC-LDPC codes in minimum-distance, cycle distribution and error-rate performance. In this letter, circulant and anti-circulant permutation matrices are used to define a class of LDPC codes, called AQC-LDPC codes, which can be considered as an special case of APM-LDPC codes. In fact, each AQC-LDPC code can be verified by a sign matrix and a slope matrix which are helpful to show each cycle in the Tanner graph by a modular linear equation. For the normal sign matrix $A$ , if −1 $\in A$ , it is shown that the corresponding AQC-LDPC code has maximum-girth 8. Finally, two explicit constructions for AQC-LDPC codes with girths 6, 8 are presented which have some benefits rather than the explicitly constructed QC and APM LDPC codes in minimum-distance, cycle distributions and bit-error-rate performances.

Randomized Serially Concatenated LDGM Codes for the Gaussian Wiretap Channel

We study the application of a special class of low-density parity-check codes to the wiretap channel. We construct a randomized coding scheme based on serially concatenated low-density generator matrix codes and their duals extending the approach used for convolutional and turbo codes. Furthermore, we propose an efficient iterative decoder for this scheme utilizing a joint iterative message passing algorithm. We demonstrate via numerical examples that this approach outperforms other available practical coding alternatives for the Gaussian wiretap channel in terms of the resulting security gap.

Explicit APM-LDPC Codes With Girths 6, 8, and 10

Recently, some attentions have been focused on a class of low-density parity-check codes from affine permutation matrices , called APM-LDPC codes, which have some advantages rather than quasi-cyclic low-density parity-check (QC-LDPC) codes in the minimum-distance, cycle distribution and error-rate performance. In this letter, first, some novel explicit constructions for exponent matrices of conventional APM-LDPC codes with girths 6, 8, and 10 are investigated, and for each given exponent matrix $E$ corresponding to an APM-LDPC code with girth $2g$ , $3\leq g\leq 5$ , a lower bound $Q=Q(E,g)$ is obtained, such that APM-LDPC codes with exponent matrix $E$ have girth at least $2g$ , for each (prime) APM size $m\geq Q$ . Then, regarding to reduce the lower bound, an improved bound $IQ$ is obtained, which is significantly better than some lower bounds reported for QC-LDPC codes with explicit constructions. Simulation results show that the constructed APM-LDPC codes outperform QC-LDPC codes with the same girth.

Searching for Binary and Nonbinary Block and Convolutional LDPC Codes

A unified approach to search for and optimize codes determined by their sparse parity-check matrices is presented. Replacing the nonzero elements of a binary parity-check matrix (the base or parent matrix) either by circulants or by companion matrices of elements from a finite field GF $(2^{m})$ , we obtain quasi-cyclic low-density parity-check (LDPC) block codes and binary images of nonbinary LDPC block codes, respectively. By substituting monomials of a formal variable $D$ , we obtain the polynomial description of an LDPC convolutional code. A set of performance measures applicable to different classes of LDPC codes is considered, and a greedy algorithm for code performance optimization is presented. The heart of the new optimization algorithm is a fast procedure for searching for LDPC codes with large girth of their Tanner graphs. For a few classes of LDPC codes, examples of codes combining good error-correcting performance with compact representation are obtained. In particular, we present optimized convolutional LDPC codes and conclude that the LDPC block codes are still superior to their convolutional counterparts if both decoding complexity and coding delay are considered. Moreover, a specific channel model can easily be embedded into the optimization loop. Thereby, the code can be optimized for a specific channel. The efficiency of such an optimization is demonstrated via an example of faster than Nyquist (FTN) signaling using LDPC codes. The FTN strategy combined with a rate $R=1/2$ LDPC code of length 64 800 optimized for effective data rate $R=3/4$ gains more than 0.5 dB compared with the standard LDPC codes of the same rate and length. The obtained gain corresponds to transmission at the capacity of the binary input additive white Gaussian noise channel. In most numerical examples, we consider codes with bidiagonal structure of the parity-check matrix. This restriction preserves low encoding complexity and allows fair comparison with codes selected for communication standards.

High‐performance binary and non‐binary Low‐density parity‐check codes based on affine permutation matrices

Low-density parity-check (LDPC) codes from affine permutation matrices, called APM-LDPC codes, are a class of LDPC codes whose parity-check matrices consist of zero matrices or APMs of the same orders. APM-LDPC codes are not quasi-cyclic (QC), in general. In this study, necessary and sufficient conditions are provided for an APM-LDPC code to have cycles of length 2l, l ≥ 2, and a deterministic algorithm is given to generate APM-LDPC codes with a given girth. Unlike Type-I conventional QC-LDPC codes, the constructed (J, L) APM-LDPC codes with the J × L all-one base matrix can achieve minimum distance greater than (J + 1)! and girth larger than 12. Moreover, the lengths of the constructed APM-LDPC codes, in some cases, are smaller than the best known lengths reported for QC-LDPC codes with the same base matrices. Another significant advantage of the constructed APM-LDPC codes is that they have remarkably fewer cycle multiplicities compared with QC-LDPC codes with the same base matrices and the same lengths. Simulation results show that the binary and non-binary constructed APM-LDPC codes with lower girth outperform QC-LDPC codes with larger girth.

Rate-compatible LDPC codes based on the PEG algorithm for relay communication systems

It is known that the progressive edge-growth (PEG) algorithm can be used to construct low-density parity-check (LDPC) codes at finite code lengths with large girths through the establishment of edges between variable and check nodes in an edge-by-edge manner. In [1], the authors derived a class of LDPC codes for relay communication systems by extending the full-diversity root-LDPC code. However, the submatrices of the parity-check matrix H corresponding to this code were constructed separately; thus, the girth of H was not optimized. To solve this problem, this paper proposes a modified PEG algorithm for use in the design of large girth and full-diversity LDPC codes. Simulation results indicated that the LDPC codes constructed using the modified PEG algorithm exhibited a more favorable frame error rate performance than did codes proposed in [1] over block-fading channels.

Photonic circuits for iterative decoding of a class of low-density parity-check codes

Photonic circuits in which stateful components are coupled via guided electromagnetic fields are natural candidates for resource-efficient implementation of iterative stochastic algorithms based on propagation of information around a graph. Conversely, such message=passing algorithms suggest novel circuit architectures for signal processing and computation that are well matched to nanophotonic device physics. Here, we construct and analyze a quantum optical model of a photonic circuit for iterative decoding of a class of low-density parity-check (LDPC) codes called expander codes. Our circuit can be understood as an open quantum system whose autonomous dynamics map straightforwardly onto the subroutines of an LDPC decoding scheme, with several attractive features: it can operate in the ultra-low power regime of photonics in which quantum fluctuations become significant, it is robust to noise and component imperfections, it achieves comparable performance to known iterative algorithms for this class of codes, and it provides an instructive example of how nanophotonic cavity quantum electrodynamic components can enable useful new information technology even if the solid-state qubits on which they are based are heavily dephased and cannot support large-scale entanglement.

Spatially coupled sparse codes on graphs: theory and practice

Since the discovery of turbo codes 20 years ago and the subsequent re-discovery of low-density parity-check codes a few years later, the field of channel coding has experienced a number of major advances. Up until that time, code designers were usually happy with performance that came within a few decibels of the Shannon Limit, primarily due to implementation complexity constraints, whereas the new coding techniques now allow performance within a small fraction of a decibel of capacity with modest encoding and decoding complexity. Due to these significant improvements, coding standards in applications as varied as wireless mobile transmission, satellite TV, and deep space communication are being updated to incorporate the new techniques. In this paper, we review a particularly exciting new class of low-density parity-check codes, called spatially-coupled codes, which promise excellent performance over a broad range of channel conditions and decoded error rate requirements.

Application of Beam Search for the decoding of one class of LDPC codes

For one class of Low-Density Parity-Check (LDPC) codes with low row weight in their parity check matrix, a new Syndrome Decoding (SD) based on the heuristic Beam Search (BS), labeled as SD-BS, is put forward to improve the error performance. First, two observations are made and verified by simulation results. One is that in the SNR region of interest, the hard-decision on the corrupted sequence yields only a handful of erroneous bits. The other is that the true error pattern for the nonzero syndrome has a high probability to survive the competition in the BS, provided sufficient beam width. Bearing these two points in mind, the decoding of LDPC codes is transformed into seeking an error pattern with the known decoding syndrome. Secondly, the effectiveness of SD-BS depends closely on how to evaluate the bit reliability. Enlightened by a bit-flipping definition in the existing literature, a new metric is employed in the proposed SD-BS. The strength of SD-BS is demonstrated via applying it on the corrupted sequences directly and the decoding failures of the Belief Propagation (BP), respectively.

LDPC codes generated by conics in the classical projective plane

We construct various classes of low-density parity-check codes using point-line incidence structures in the classical projective plane PG(2,q). Each incidence structure is based on the various classes of points and lines created by the geometry of a conic in the plane. For each class, we prove various properties about dimension and minimum distance. Some arguments involve the geometry of two conics in the plane. As a result, we prove, under mild conditions, the existence of two conics, one entirely internal or external to the other. We conclude with some simulation data to exhibit the effectiveness of our codes.

Design of high-performance low-density parity-check codes using interleaver approach

Interleaver description of parity-check matrix is proposed for the design of high-performance low-density parity-check (LDPC) codes. Based on the S-random interleaver and the dividable S-random interleaver used in turbo codes, two classes of LDPC codes, the g-random codes and the g-random structured codes, are proposed to improve the performance in the waterfall region and slow down the onset of the error floor.

Design of Efficiently Encodable Moderate-Length High-Rate Irregular LDPC Codes

This paper presents a new class of irregular low-density parity-check (LDPC) codes of moderate length (10/sup 3//spl les/n/spl les/10/sup 4/) and high rate (R/spl ges/3/4). Codes in this class admit low-complexity encoding and have lower error-rate floors than other irregular LDPC code-design approaches. It is also shown that this class of LDPC codes is equivalent to a class of systematic serial turbo codes and is an extension of irregular repeat-accumulate codes. A code design algorithm based on the combination of density evolution and differential evolution optimization with a modified cost function is presented. Moderate-length, high-rate codes with no error-rate floors down to a bit-error rate of 10/sup -9/ are presented. Although our focus is on moderate-length, high-rate codes, the proposed coding scheme is applicable to irregular LDPC codes with other lengths and rates.

Low-density parity-check codes based on finite geometries: a rediscovery and new results

This paper presents a geometric approach to the construction of low-density parity-check (LDPC) codes. Four classes of LDPC codes are constructed based on the lines and points of Euclidean and projective geometries over finite fields. Codes of these four classes have good minimum distances and their Tanner (1981) graphs have girth 6. Finite-geometry LDPC codes can be decoded in various ways, ranging from low to high decoding complexity and from reasonably good to very good performance. They perform very well with iterative decoding. Furthermore, they can be put in either cyclic or quasi-cyclic form. Consequently, their encoding can be achieved in linear time and implemented with simple feedback shift registers. This advantage is not shared by other LDPC codes in general and is important in practice. Finite-geometry LDPC codes can be extended and shortened in various ways to obtain other good LDPC codes. Several techniques of extension and shortening are presented. Long extended finite-geometry LDPC codes have been constructed and they achieve a performance only a few tenths of a decibel away from the Shannon theoretical limit with iterative decoding.