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With the massive amount of data produced and stored each year, reliable storage and retrieval of information is more crucial than ever. Robust coding and decoding techniques are critical for correcting errors and maintaining data integrity. Comprising chapters thoughtfully selected from the highly popular Coding and Signal Processing for Magnetic Recording Systems, Advanced Error Control Techniques for Data Storage Systems is a finely focused reference to the state-of-the-art error control and modulation techniques used in storage devices. The book begins with an introduction to error control codes, explaining the theory and basic concepts underlying the codes. Building on these concepts, the discussion turns to modulation codes, paying special attention to run-length limited sequences, followed by maximum transition run (MTR) and spectrum shaping codes. It examines the relationship between constrained codes and error control and correction systems from both code-design and architectural perspectives as well as techniques based on convolution codes. With a focus on increasing data density, the book also explores multi-track systems, soft decision decoding, and iteratively decodable codes such as Low-Density Parity-Check (LDPC) Codes, Turbo codes, and Turbo Product Codes. Advanced Error Control Techniques for Data Storage Systems offers a comprehensive collection of theory and techniques that is ideal for specialists working in the field of data storage systems.
Nowadays it is hard to find an electronic device which does not use codes: for example, we listen to music via heavily encoded audio CD's and we watch movies via encoded DVD's. There is at least one area where the use of encoding/decoding is not so developed, yet: Flash non-volatile memories. Flash memory high-density, low power, cost effectiveness, and scalable design make it an ideal choice to fuel the explosion of multimedia products, like USB keys, MP3 players, digital cameras and solid-state disk. In ECC for Non-Volatile Memories the authors expose the basics of coding theory needed to understand the application to memories, as well as the relevant design topics, with reference to both NOR and NAND Flash architectures. A collection of software routines is also included for better understanding. The authors form a research group (now at Qimonda) which is the typical example of a fruitful collaboration between mathematicians and engineers.
Error-control coding is a special subject with its own history and arithmetic systems. The theory and usage of error-control codes relate to the protection of digital information against errors that occur during data transmission and storage. Error correction coding attaches redundancy to the data at the system's error correction encoder and uses that redundancy to correct erroneous data at the error correction decoder.This thesis focuses on error correcting codes and the hardware implementation of two error-control codes - Reed-Solomon (RS) codes and Viterbi's algorithm. Prior to emphasizing on these two codes, a brief description of various other types of error correcting schemes is presented. A simple (15, 9) RS code and a (4, 1, 2) convolutional code are taken to elaborate the encoding and decoding processes for these error correcting codes. The primary objective of this thesis is to provide a simple and efficient hardware for reliably transmitting and receiving message bits across a communication channel.
For introductory graduate courses in coding for telecommunications engineering, digital communications. This introductory text on error control coding focuses on key implementation issues and performance analysis with applications valuable to both mathematicians and engineers.
This book discusses both the theory and practical applications of self-correcting data, commonly known as error-correcting codes. The applications included demonstrate the importance of these codes in a wide range of everyday technologies, from smartphones to secure communications and transactions. Written in a readily understandable style, the book presents the authors’ twenty-five years of research organized into five parts: Part I is concerned with the theoretical performance attainable by using error correcting codes to achieve communications efficiency in digital communications systems. Part II explores the construction of error-correcting codes and explains the different families of codes and how they are designed. Techniques are described for producing the very best codes. Part III addresses the analysis of low-density parity-check (LDPC) codes, primarily to calculate their stopping sets and low-weight codeword spectrum which determines the performance of th ese codes. Part IV deals with decoders designed to realize optimum performance. Part V describes applications which include combined error correction and detection, public key cryptography using Goppa codes, correcting errors in passwords and watermarking. This book is a valuable resource for anyone interested in error-correcting codes and their applications, ranging from non-experts to professionals at the forefront of research in their field. This book is open access under a CC BY 4.0 license.
Error correcting coding is often analyzed in terms of its application to the separate levels within the data network in isolation from each other. In this fresh approach, the authors consider the data network as a superchannel (a multi-layered entity) which allows error correcting coding to be evaluated as it is applied to a number of network layers as a whole. By exposing the problems of applying error correcting coding in data networks, and by discussing coding theory and its applications, this original technique shows how to correct errors in the network through joint coding at different network layers. Discusses the problem of reconciling coding applied to different layers using a superchannel approach Includes thorough coverage of all the key codes: linear block codes, Hamming, BCH and Reed-Solomon codes, LDPC codes decoding, as well as convolutional, turbo and iterative coding Considers new areas of application of error correcting codes such as transport coding, code-based cryptosystems and coding for image compression Demonstrates how to use error correcting coding to control such important data characteristics as mean message delay Provides theoretical explanations backed up by numerous real-world examples and practical recommendations Features a companion website containing additional research results including new constructions of LDPC codes, joint error-control coding and synchronization, Reed-Muller codes and their list decoding By progressing from theory through to practical problem solving, this resource contains invaluable advice for researchers, postgraduate students, engineers and computer scientists interested in data communications and applications of coding theory.
An accessible textbook that uses step-by-step explanations, relatively easy mathematics and numerous examples to aid student understanding.
In order to meet the demands of data-hungry applications, modern data storage systems are expected to be increasingly denser. This is a challenging endeavor, and storage engineers are continuously trying to provide novel technologies. However, these new technologies are typically associated with an increase in the number and types of errors, making the goal of securing highly-reliable dense storage devices a tricky challenge. This dissertation focuses on analyzing the errors in addition to providing novel and efficient error correcting coding schemes that are capable of overcoming the aforementioned challenge. In particular, through informed exploitation of the underlying channel characteristics of the storage device being studied, we provide frameworks for systematically generating error correcting codes with mathematical guarantees that offer performance improvements in orders of magnitude relative to the prior state-of-the-art. First, we present a technique to predict the performance of codes given the existence of certain error-prone structures in the graph representation of these codes. Next, we introduce a general framework for the code optimization of non-binary graph-based codes, which works for various interesting channels. Finally, we derive an approach to design high performance spatially-coupled codes particularly for magnetic recording applications. Our frameworks are based on mathematical tools drawn from coding theory and information theory, and rely on advanced mathematical techniques from probability theory, linear algebra, graph theory, combinatorics, and optimization. The proposed frameworks have a vast variety of applications that include both magnetic recording and Flash memory systems. Our frameworks lead to a practical, effective tool for storage engineers to use multi-dimensional storage devices with confidence.