Using partial unit memory codes to improve distance properties of woven turbo codes

Partial unit memory (PUM) codes are reputed for their excellent distance properties and lower decoding complexity compared to equivalent convolutional codes. Woven turbo codes (WTCs) are constructed, which outperform turbo codes, using component PUM codes. Simulation results confirm that WTCs based on PUM codes outperform those based on equivalent convolutional codes, as reflected by their respective minimum distances, which is also calculated.     

Active distances for convolutional codes

A family of active distance measures for general convolutional codes is defined. These distances are generalizations of the extended distances introduced by Thommesen and Justesen (1983) for unit memory convolutional codes. It is shown that the error correcting capability of a convolutional code is determined by the active distances. The ensemble of periodically time-varying convolutional codes is defined and lower bounds on the active distances are derived for this ensemble. The active distances are very useful in the analysis of concatenated convolutional encoders     

Tailbiting codes obtained via convolutional codes with large active distance-slopes

The slope of the active distances is an important parameter when investigating the error-correcting capability of convolutional codes and the distance behavior of concatenated convolutional codes. The slope of the active distances is equal to the minimum average weight cycle in the state-transition diagram of the encoder. A general upper bound on the slope depending on the free distance of the convolutional code and new upper bounds on the slope of special classes of binary convolutional codes are derived. Moreover, a search technique, resulting in new tables of rate R=1/2 and rate R=1/3 convolutional encoders with high memories and large active distance-slopes is presented. Furthermore, we show that convolutional codes with large slopes can be used to obtain new tailbiting block codes with large minimum distances. Tables of rate R=1/2 and rate R=1/3 tailbiting codes with larger minimum distances than the best previously known quasi-cyclic codes are given. Two new tailbiting codes also have larger minimum distances than the best previously known binary linear block codes with same size and length. One of them is also superior in terms of minimum distance to any previously known binary nonlinear block code with the same set of parameters.     

BCH convolutional codes

Using a new parity-check matrix, a class of convolutional codes with a designed free distance is introduced. This new class of codes has many characteristics of BCH block codes, therefore, we call these codes BCH convolutional codes     

Implementation aspects of LDPC convolutional codes

Potentially large storage requirements and long initial decoding delays are two practical issues related to the decoding of low-density parity-check (LDPC) convolutional codes using a continuous pipeline decoder architecture. In this paper, we propose several reduced complexity decoding strategies to lessen the storage requirements and the initial decoding delay without significant loss in performance. We also provide bit error rate comparisons of LDPC block and LDPC convolutional codes under equal processor (hardware) complexity and equal decoding delay assumptions. A partial syndrome encoder realization for LDPC convolutional codes is also proposed and analyzed. We construct terminated LDPC convolutional codes that are suitable for block transmission over a wide range of frame lengths. Simulation results show that, for terminated LDPC convolutional codes of sufficiently large memory, performance can be improved by increasing the density of the syndrome former matrix.     

LDPC block and convolutional codes based on circulant matrices

A class of algebraically structured quasi-cyclic (QC) low-density parity-check (LDPC) codes and their convolutional counterparts is presented. The QC codes are described by sparse parity-check matrices comprised of blocks of circulant matrices. The sparse parity-check representation allows for practical graph-based iterative message-passing decoding. Based on the algebraic structure, bounds on the girth and minimum distance of the codes are found, and several possible encoding techniques are described. The performance of the QC LDPC block codes compares favorably with that of randomly constructed LDPC codes for short to moderate block lengths. The performance of the LDPC convolutional codes is superior to that of the QC codes on which they are based; this performance is the limiting performance obtained by increasing the circulant size of the base QC code. Finally, a continuous decoding procedure for the LDPC convolutional codes is described.     

Woven codes with outer warp: variations, design, and distanceproperties

We consider convolutional and block encoding schemes which are variations of woven codes with outer warp. We propose methods to evaluate the distance characteristics of the considered codes on the basis of the active distances of the component codes. With this analytical bounding technique, we derived lower bounds on the minimum (or free) distance of woven convolutional codes, woven block codes, serially concatenated codes, and woven turbo codes. Next, we show that the lower bound on the minimum distance can be improved if we use designed interleaving with unique permutation functions in each row of the warp of the woven encoder. Finally, with the help of simulations, we get upper bounds on the minimum distance for some particular codes and then investigate their performance in the Gaussian channel. Throughout this paper, we compare all considered encoding schemes by means of examples, which illustrate their distance properties     

高性能时不变LDPC卷积码构造算法研究

该文基于由QC-LDPC码获得时不变LDPC卷积码的环同构方法,设计了用有限域上元素直接获得时不变LDPC卷积码多项式矩阵的新算法。以MDS卷积码为例,给出了一个具体的构造过程。所提构造算法可确保所获得的时不变LDPC卷积码具有快速编码特性、最大可达编码记忆以及设计码率。基于滑动窗口的BP译码算法在AWGN信道上的仿真结果表明,该码具有较低的误码平台和较好的纠错性能。     

Srivastava codes

Srivastava codes, a class of linear noncyclic error-correcting codes, offer performance potentially superior tO that of comparable BCH codes. Their properties are investigated by equivalence classification and subsequent computer evaluation of their weight spectra. In the process a constructive upper bound is obtained on the number of equivalence classes of Srivastava codes, a class of binary Srivastava codes whose parity-check matrices have row rank less than the maximum, and a class of binary double-error,correcting codes w!th highly structured parity-check matrices. A number of shortened binary Srivastava codes with minimum distances superior to those of the best comparable linear codes known are also presented.     

Strongly-MDS convolutional codes

Maximum-distance separable (MDS) convolutional codes have the property that their free distance is maximal among all codes of the same rate and the same degree. In this paper, a class of MDS convolutional codes is introduced whose column distances reach the generalized Singleton bound at the earliest possible instant. Such codes are called strongly-MDS convolutional codes. They also have a maximum or near-maximum distance profile. The extended row distances of these codes will also be discussed briefly.     

New optimal partial unit memory codes based on extended BCH codes

Some new optimal binary partial unit memory codes are presented. The codes are constructed from extended BCH codes. A general method for constructing PUM codes based on extended RS and BCH codes is described.<>     

Hybrid block- self-orthogonal convolutional codes

Two convolutional-code construction schemes that utilize block codes are given. In the first method the generators of a self-orthogonal convolutional code (SOCC) are expanded. The generators of a block code whose block length is longer than that of the SOCC code replace the nonzero blocks of the convolutional code. The zero blocks are extended to the longer block length. There results a convolutional code whose blocks are self-orthogonal and which has a lower transmission rate. In the second scheme the parity constraints of an SOCC are expanded. The parity constraints of a block code replace some of the individual nonzero elements of the SOCC parity-check matrix, so that the convolutional code rate is greater than the block code rate. The resulting codes retain the SOCC advantages of simple implementation and limited error propagation. Both the encoding and the decoding can be based on the underlying block code. If a block code is majority decodable, then the resulting "hybrid" codes are majority decodable. Optimum majority-decodable block codes with up to five information bits per block are given, and from these codes several majority-decodable convolutional codes that are "optimum" with respect to the proposed construction are obtained.     

Finite field construction for quasi-cyclic LDPC convolutional codes with cyclic 2-D MDS codes

The parity-check matrices for quasi-cyclic low-density parity-check convolutional (QC-LDPC-C) codes have different characteristics of time-varying periodicity and need to realize fast encoding. The finite field construction method for QC-LDPC-C codes with cyclic two-dimensional maximum distance separable (2-D MDS) codes is proposed using the base matrix framework and matrix unwrapping, thus the constructed parity-check matrices are free of length-4 cycles. The unwrapped matrices are constructed respectively based on different cyclic 2-D MDS codes for the case of matrix period less than or greater than constraint block length, and construction examples are given. LDPC-C codes with different periodicity characteristics are compared with QC-LDPC-C codes constructed with the proposed method. Experimental results show that QC-LDPC-C codes with the proposed method outperform the other codes and have lower encoding and decoding complexity.

     

Bounded minimum distance decoding of unit memory codes

We propose an algorithm for bounded minimum distance decoding of (partial) unit memory codes up to half the “designed” extended row distance. It makes use of a reduced trellis with the nodes found by bounded minimum distance decoding of the block codes used in the unit memory code. The results can be extended to general multimemory codes. The complexity of this algorithm is upper bounded by 2(d¯ ₁^r-2d_α) times the complexity of the bounded minimum distance decoder of the block codes in the unit memory code. Here d_α is the linear increase of the designed extended row distance d¯_i^r     

On ensembles of low-density parity-check codes: asymptotic distancedistributions

We derive expressions for the average distance distributions in several ensembles of regular low-density parity-check codes (LDPC). Among these ensembles are the standard one defined by matrices having given column and row sums, ensembles defined by matrices with given column sums or given row sums, and an ensemble defined by bipartite graphs     

Bounds on distances and error exponents of unit memory codes

Binary unit memory codes, originally introduced by Lee, are investigated. A few examples of constant unit memory codes are given and bounds on the distance profile and the free distances are discussed. For time-varying codes asymptotic lower bounds on the distance profile and the free distance are given. The error probability for the codes, used on a memoryless binary-input, output-symmetric channel, is asymptotically upper bounded. The asymptotic results for the free distance and the error probability, which are in some respects better than for conventional convolutional codes, are interpreted by Forney's inverse concatenation construction.     

Efficient encoding of low-density parity-check codes

Low-density parity-check (LDPC) codes can be considered serious competitors to turbo codes in terms of performance and complexity and they are based on a similar philosophy: constrained random code ensembles and iterative decoding algorithms. We consider the encoding problem for LDPC codes. More generally we consider the encoding problem for codes specified by sparse parity-check matrices. We show how to exploit the sparseness of the parity-check matrix to obtain efficient encoders. For the (3,6)-regular LDPC code, for example, the complexity of encoding is essentially quadratic in the block length. However, we show that the associated coefficient can be made quite small, so that encoding codes even of length n≃100000 is still quite practical. More importantly, we show that “optimized” codes actually admit linear time encoding     

Finite-length analysis of low-density parity-check codes on thebinary erasure channel

In this paper, we are concerned with the finite-length analysis of low-density parity-check (LDPC) codes when used over the binary erasure channel (BEC). The main result is an expression for the exact average bit and block erasure probability for a given regular ensemble of LDPC codes when decoded iteratively. We also give expressions for upper bounds on the average bit and block erasure probability for regular LDPC ensembles and the standard random ensemble under maximum-likelihood (ML) decoding. Finally, we present what we consider to be the most important open problems in this area     

Partitioned linear block codes for computer memory with 'stuck-at' defects

Linear block codes are studied for improving the reliability of message storage in computer memory with stuck-at defects and noise. The case when the side information about the state of the defects is available to the decoder or to the encoder is considered. In the former case, stuck-at cells act as erasures so that techniques for decoding linear block codes for erasures and errors can be directly applied. We concentrate on the complimentary problem of incorporating stuck-at information in the encoding of linear block codes. An algebraic model for stuck-at defects and additive errors is presented. The notion of a "partitioned" linear block code is introduced to mask defects known at the encoder and to correct random errors at the decoder. The defect and error correction capability of partitioned linear block codes is characterized in terms of minimum distances. A class of partitioned cyclic codes is introduced. A BCH-type bound for these cyclic codes is derived and employed to construct partitioned linear block codes with specified bounds on the minimum distances. Finally, a probabilistic model for the generation of stuck-at cells is presented. It is shown that partitioned linear block codes achieve the Shannon capacity for a computer memory with symmetric defects and errors.     

Woven convolutional codes .I. Encoder properties

Encoders for convolutional codes with large free distances can be constructed by combining several less powerful convolutional encoders. This paper is devoted to constructions in which the constituent convolutional codes are woven together in a manner that resembles the structure of a fabric. The general construction is called twill and it is described together with two special cases, viz., woven convolutional encoders with outer warp and with inner warp. The woven convolutional encoders inherit many of their structural properties, such as minimality and catastrophicity, from their constituent encoders. For all three types of woven convolutional codes upper and lower bounds on their free distances as well as lower bounds on the active distances of their encoders are derived