Download or read book Design and Analysis of Graph based Codes Using Algebraic Lifts and Decoding Networks written by Allison Beemer and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Error-correcting codes seek to address the problem of transmitting information efficiently and reliably across noisy channels. Among the most competitive codes developed in the last 70 years are low-density parity-check (LDPC) codes, a class of codes whose structure may be represented by sparse bipartite graphs. In addition to having the potential to be capacity-approaching, LDPC codes offer the significant practical advantage of low-complexity graph-based decoding algorithms. Graphical substructures called trapping sets, absorbing sets, and stopping sets characterize failure of these algorithms at high signal-to-noise ratios.
Download or read book Algebraic Graph Algorithms written by K. Erciyes and published by Springer Nature. This book was released on 2021-11-17 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook discusses the design and implementation of basic algebraic graph algorithms, and algebraic graph algorithms for complex networks, employing matroids whenever possible. The text describes the design of a simple parallel matrix algorithm kernel that can be used for parallel processing of algebraic graph algorithms. Example code is presented in pseudocode, together with case studies in Python and MPI. The text assumes readers have a background in graph theory and/or graph algorithms.
Download or read book Fundamentals of Codes Graphs and Iterative Decoding written by Stephen B. Wicker and published by Springer Science & Business Media. This book was released on 2006-04-18 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamentals of Codes, Graphs, and Iterative Decoding is an explanation of how to introduce local connectivity, and how to exploit simple structural descriptions. Chapter 1 provides an overview of Shannon theory and the basic tools of complexity theory, communication theory, and bounds on code construction. Chapters 2 - 4 provide an overview of "classical" error control coding, with an introduction to abstract algebra, and block and convolutional codes. Chapters 5 - 9 then proceed to systematically develop the key research results of the 1990s and early 2000s with an introduction to graph theory, followed by chapters on algorithms on graphs, turbo error control, low density parity check codes, and low density generator codes.
Download or read book Studies on Graph based Coding Systems written by Jing Sun and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: To make full use of the valuable radio spectrum, one of the targets of communications system design is to convey as much information as possible through the spectrum (the channel) allocated for the purpose. For a given channel, the amount of information that can be passed through it is upper bounded by the well-known Shannon channel capacity. The invention of turbo codes in 1993 was a key step in the 50-year effort to design good coding schemes achieving the Shannon capacity. Since then, other coding schemes with similar performance, such as Low Density Parity Check (LDPC) codes and turbo product codes, have been re-discovered or invented. The common characteristics of these codes are that they all can be represented by a large (pseudo- )random graph, and iteratively decoded. In this dissertation, we treat three topics in the design and analysis of the two most important graph-based coding schemes: turbo codes and LDPC codes. Together with two component convolutional codes, an interleaver is a key component of a turbo code. We introduce a class of deterministic interleavers for turbo codes based on permutation polynomials over Z (sub)N . It is observed that the performance of a turbo code using these permutation polynomial-based interleavers is usually dominated by a subset of input weight 2m error events. Due to the structure of these interleavers, we derive a simple method to find the weight spectrum of those error events. Therefore good permutation polynomials can be searched for a given component code to achieve better performance. LDPC codes can be constructed using an interleaver. In a previous work, the use of maximum length linear congruential sequences (MLLCS) has been proposed for the construction of interleavers for regular LDPC codes with data node degree 3. Since the smallest loop size (girth) is a key characteristic of the graph of the LDPC code, a sufficient condition on the parameters of the MLLCS to generate a graph with girth larger than 4 is given. We extend the sufficient condition to general irregular LDPC codes and also provide sufficient conditions to guarantee even larger girth. It is observed that the error floor of LDPC code (bit error performance at high signal-to-noise ratios) is usually caused by trapping sets, which are sets of data nodes that cannot be corrected by the iterative decoder. We develop an approximated linear system model for the iterative decoding process in a trapping set. Then the probability that the trapping set can be corrected can be estimated by observing the response of the linear system. Using the idea from the analysis of the linear system, the iterative decoder for regular LDPC codes can be slightly modified to greatly decrease the error floor.
Download or read book Algebraic Coding Theory and Information Theory written by Alexei Ashikhmin and published by American Mathematical Soc.. This book was released on 2005 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: In these papers associated with the workshop of December 2003, contributors describe their work in fountain codes for lossless data compression, an application of coding theory to universal lossless source coding performance bounds, expander graphs and codes, multilevel expander codes, low parity check lattices, sparse factor graph representations of Reed-Solomon and related codes. Interpolation multiplicity assignment algorithms for algebraic soft- decision decoding of Reed-Solomon codes, the capacity of two- dimensional weight-constrained memories, networks of two-way channels, and a new approach to the design of digital communication systems. Annotation :2005 Book News, Inc., Portland, OR (booknews.com).
Download or read book Design Techniques for Graph based Error correcting Codes and Their Applications written by Ching Fu Lan and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In Shannon's seminal paper, "A Mathematical Theory of Communication", he defined "Channel Capacity" which predicted the ultimate performance that transmission systems can achieve and suggested that capacity is achievable by error-correcting (channel) coding. The main idea of error-correcting codes is to add redundancy to the information to be transmitted so that the receiver can explore the correlation between transmitted information and redundancy and correct or detect errors caused by channels afterward. The discovery of turbo codes and rediscovery of Low Density Parity Check codes (LDPC) have revived the research in channel coding with novel ideas and techniques on code concatenation, iterative decoding, graph-based construction and design based on density evolution. This dissertation focuses on the design aspect of graph-based channel codes such as LDPC and Irregular Repeat Accumulate (IRA) codes via density evolution, and use the technique (density evolution) to design IRA codes for scalable image/video communication and LDPC codes for distributed source coding, which can be considered as a channel coding problem. The first part of the dissertation includes design and analysis of rate-compatible IRA codes for scalable image transmission systems. This part presents the analysis with density evolution the effect of puncturing applied to IRA codes and the asymptotic analysis of the performance of the systems. In the second part of the dissertation, we consider designing source-optimized IRA codes. The idea is to take advantage of the capability of Unequal Error Protection (UEP) of IRA codes against errors because of their irregularities. In video and image transmission systems, the performance is measured by Peak Signal to Noise Ratio (PSNR). We propose an approach to design IRA codes optimized for such a criterion. In the third part of the dissertation, we investigate Slepian-Wolf coding problem using LDPC codes. The problems to be addressed include coding problem involving multiple sources and non-binary sources, and coding using multi-level codes and nonbinary codes.
Download or read book Algebraic Low density Parity check Codes written by Qiuju Diao and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The ever-growing needs for cheaper, faster, and more reliable communication systems have forced many researchers to seek means to attain the ultimate limits on reliable communications. Low densityparity-check (LDPC) codes are currently the most promising coding technique to achieve the Shannon capacities for a wide range of channels. Many LDPC codes have been chosen as the standard codes for various next generations of communication systems and they are appearing in recent data storage products. More applications are expected to come.Major methods for constructing LDPC codes can be divided into two general categories, graphtheoretic-based methods (using computer search) and algebraic methods. Each type of constructions has its advantages and disadvantages in terms overall error performance, encoding and decoding implementations. In general, algebraically constructed LDPC codes have lower error-floor and their decoding using iterative message-passing algorithms converges at a much faster rate than the LDPC codes constructed using a graph theoretic-based method. Furthermore, it is much easier to constructalgebraic LDPC codes with large minimum distances.This research project is set up to investigate several important aspects of algebraic LDPC codes for the purpose of achieving overall good error performance required for future high-speed communication systems and high-density data storage systems. The subjects to be investigated include: (1) new constructions of algebraic LDPC codes based on finite geometries; (2) analysis of structural properties of algebraic LDPC codes, especially the trapping set structure that determines how lowthe error probability of a given LDPC code can achieve; (3) construction of algebraic LDPC codes and design coding techniques for correcting combinations of random errors and erasures that occursimultaneously in many physical communication and storage channels; and (4) analysis and construction of algebraic LDPC codes in transform domain.Research effort has resulted in important findings in all four proposed research subjects which may have a significant impact on future generations of communication and storage systems andadvance the state-of-the-art of channel coding theory.
Download or read book Turbo like Codes written by Aliazam Abbasfar and published by Springer. This book was released on 2010-10-19 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces turbo error correcting concept in a simple language, including a general theory and the algorithms for decoding turbo-like code. It presents a unified framework for the design and analysis of turbo codes and LDPC codes and their decoding algorithms. A major focus is on high speed turbo decoding, which targets applications with data rates of several hundred million bits per second (Mbps).
Download or read book Applications of Graph based Codes in Networks written by Badri Narayanan Vellambi and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The conception of turbo codes by Berrou et al. has created a renewed interest in modern graph-based codes. Several encouraging results that have come to light since then have fortified the role these codes shall play as potential solutions for present and future communication problems.
Download or read book Decoding of algebraic geometry codes and the use of neural networks for finite field written by and published by . This book was released on 1902 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Este trabalho propõe um algoritmo para decodificação de códigos de geometria algébrica. Usando as propriedades geométricas da curva que define um código de Goppa com distância projetada d, método permite decodificar até [d 1/ 2] erros em palavra recebida, sem esforço computacional adicional. As curvas de F.K. Schimdt são usada para construir uma nova classe de códigos de geometria algébrica, algumas propriedades destes novos códigos são apresentadas. Redes neurais não ortodoxas do tipo feedforward e não treinadas são usadas para construir circuitos que permitem calcular logaritmos de Zech eficientemente e, portanto, realizar aritmética em corpos finitos sem uso de tabelas.
Download or read book Code Representation and Performance of Graph Based Decoding written by Junsheng Han and published by . This book was released on 2008 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: Key to the success of modern error correcting codes is the effectiveness of message-passing iterative decoding (MPID). Unlike maximum-likelihood (ML) decoding, the performance of MPID depends not only on the code, but on how the code is represented. In particular, the performance of MPID is potentially improved by using a redundant representation. We focus on Tanner graphs and study combinatorial structures therein that help explain the performance disparity among different representations of the same code. Emphasis is placed on the complexity-performance tradeoff, as more and more check nodes are allowed in the graph. Our discussion applies to MPID as well as linear programming decoding (LPD), which we collectively refer to as graph-based decoding. On an erasure channel, it is well-known that the performance of MPID or LPD is determined by stopping sets. Following Schwartz and Vardy, we define the stopping redundancy as the smallest number of check nodes in a Tanner graph such that smallest size of a non-empty stopping set is equal to the minimum Hamming distance of the code. Roughly speaking, stopping redundancy measures the complexity requirement (in number of check nodes) for MPID of a redundant graph representation to achieve performance comparable to ML decoding (up to a constant factor for small channel erasure probability). General upper bounds on stopping redundancy are obtained. One of our main contribution is a new upper bound based on probabilistic analysis, which is shown to be by far the strongest. From this bound, it can be shown, for example, that for a fixed minimum distance, the stopping redundancy grows just linearly with the redundancy (codimension). Specific results on the stopping redundancy of Golay and Reed-Muller codes are also obtained. We show that the stopping redundancy of maximum distance separable (MDS) codes is bounded in between a Turan number and a single-exclusion (SE) number --- a purely combinatorial quantity that we introduce. By studying upper bounds on the SE number, new results on the stopping redundancy of MDS codes are obtained. Schwartz and Vardy conjecture that the stopping redundancy of an MDS code should only depend on its length and minimum distance. Our results provide partial confirmation, both exact and asymptotic, to this conjecture. Stopping redundancy can be large for some codes. We observe that significantly fewer checks are needed if a small number of small stopping sets are allowed. These small stopping sets can then be dealt with by ``guessing'' during the iterative decoding process. Correspondingly, the guess-g stopping redundancy is defined and it is shown that the savings in number of required check nodes are potentially significant. Another theoretically interesting question is when MPID of a Tanner graph achieves the same word error rate an ML decoder. This prompts us to define and study ML redundancy. Applicability and possible extensions of the current work to a non-erasure channel are discussed. A framework based on pseudo-codewords is considered and shown to be relevant. However, it is also observed that the polytope characterization of pseudo-codewords is not complete enough to be an accurate indicator of MPID performance. Finally, in a separate piece of work, the probability of undetected error (PUE) for over-extended Reed-Solomon codes is studied through the weight distribution bounds of the code. The resulting PUE expressions are shown to be tight in a well-defined sense.
Download or read book Iterative Decoding of Codes on Graphs written by Sundararajan Sankaranarayanan and published by . This book was released on 2006 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: The growing popularity of a class of linear block codes called the low-density parity-check (LDPC) codes can be attributed to the low complexity of the iterative decoders, and their potential to achieve performance very close to the Shannon capacity. This makes them an attractive candidate for ECC applications in communication systems. This report proposes methods to systematically construct regular and irregular LDPC codes. A class of regular LDPC codes are constructed from incidence structures in finite geometries like projective geometry and affine geometry. A class of irregular LDPC codes are constructed by systematically splitting blocks of balanced incomplete block designs to achieve desired weight distributions. These codes are decoded iteratively using message-passing algorithms, and the performance of these codes for various channels are presented in this report. The application of iterative decoders is generally limited to a class of codes whose graph representations are free of small cycles. Unfortunately, the large class of conventional algebraic codes, like RS codes, has several four cycles in their graph representations. This report proposes an algorithm that aims to alleviate this drawback by constructing an equivalent graph representation that is free of four cycles. It is theoretically shown that the four-cycle free representation is better suited to iterative erasure decoding than the conventional representation. Also, the new representation is exploited to realize, with limited success, iterative decoding of Reed-Solomon codes over the additive white Gaussian noise channel. Wiberg, Forney, Richardson, Koetter, and Vontobel have made significant contributions in developing theoretical frameworks that facilitate finite length analysis of codes. With an exception of Richardson's, most of the other frameworks are much suited for the analysis of short codes. In this report, we further the understanding of the failures in iterative decoders for the binary symmetric channel. The failures of the decoder are classified into two categories by defining trapping sets and propagating sets. Such a classification leads to a successful estimation of the performance of codes under the Gallager B decoder. Especially, the estimation techniques show great promise in the high signal-to-noise ratio regime where the simulation techniques are less feasible.
Download or read book On Linear Programming Based Decoding of Graph based Codes written by Idan Goldenberg and published by . This book was released on 2013 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book LDPC Code Designs Constructions and Unification written by Juane Li and published by Cambridge University Press. This book was released on 2017 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, leading authorities unify algebraic- and graph-based LDPC code designs and constructions into a single theoretical framework.
Download or read book Channel Codes written by William Ryan and published by Cambridge University Press. This book was released on 2009-09-17 with total page 709 pages. Available in PDF, EPUB and Kindle. Book excerpt: Channel coding lies at the heart of digital communication and data storage, and this detailed introduction describes the core theory as well as decoding algorithms, implementation details, and performance analyses. In this book, Professors Ryan and Lin provide clear information on modern channel codes, including turbo and low-density parity-check (LDPC) codes. They also present detailed coverage of BCH codes, Reed-Solomon codes, convolutional codes, finite geometry codes, and product codes, providing a one-stop resource for both classical and modern coding techniques. Assuming no prior knowledge in the field of channel coding, the opening chapters begin with basic theory to introduce newcomers to the subject. Later chapters then extend to advanced topics such as code ensemble performance analyses and algebraic code design. 250 varied and stimulating end-of-chapter problems are also included to test and enhance learning, making this an essential resource for students and practitioners alike.
Download or read book Gossip Algorithms written by Devavrat Shah and published by Now Publishers Inc. This book was released on 2009 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: A systematic survey of many of these recent results on Gossip network algorithms.
Download or read book Dissertation Abstracts International written by and published by . This book was released on 2005 with total page 796 pages. Available in PDF, EPUB and Kindle. Book excerpt:
