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About 5,142 papers for “convolutional codes”

Convolutional Codes

Jakub Skalický · Digital Repository (National Repository of Grey Literature) · 2009

Cited by 0

Convolutional Codes

Gaurav Sharma, Rna Structure Analysis Motivation · 2013

◮ RNA, noncoding RNA, RNA structure and its significance ◮ RNA structure prediction ◮ Single/Multiple sequence methods

Cited by 0

Convolutional Codes

Todd K. Moon · 2005

The prelims comprise: Introduction and Basic Notation Definition of Codes and Equivalent Codes Decoding Convolutional Codes Some Performance Results Error Analysis for Convolutional Codes Tables of Good Codes Puncturing Suboptimal Decoding Algorithms for Convolutional Codes Convolutional Codes as Block Codes Trellis Representations of Block and Cyclic Codes Exercises References

Cited by 3

Convolutional Codes

Richard E. Blahut · Cambridge University Press eBooks · 2003

To encode an infinite stream of data symbols with a block code, the datastream is broken into blocks, each of k data symbols, called datawords. The block code encodes each block of k data symbols into a block of n code symbols, called a codeword. The codewords are concatenated to form an infinite stream of code symbols.

Cited by 0

Convolutional Codes

Christian Schlegel, Lance C. Pérez · 2004

In this chapter, we bring together the main results that have evolved over the years and are specific to convolutional codes. They mainly relate to encoder realizations and classification as well as minimality of finite-state representations. We draw strongly on the elegant summary by Johannesson and Wan. Their work, in turn, mainly draws on the ground-breaking exposition by Forney, who presents a rich algebraic structure of convolutional codes and encoders. In the appendix 4.A, we generate a sequence of matrix operations which turn P into the diagonal matrix Γ according to Theorem 4.5.

Cited by 0

Convolutional Codes

Wayne Stark · Cambridge University Press eBooks · 2023

Master the fundamentals of digital communications systems with this accessible and hands-on introductory textbook, carefully interweaving theory and practice. The just-in-time approach introduces essential background as needed, keeping academic theory firmly linked to practical applications. The example-led teaching frames key concepts in the context of real-world systems, such as 5G, WiFi, and GPS. Stark provides foundational material on the trade-offs between energy and bandwidth efficiency, giving students a solid grounding in the fundamental challenges of designing digital communications systems. Features include over 300 illustrative figures, 80 examples, and 130 end-of-chapter problems to reinforce student understanding, with solutions for instructors. Accompanied online by lecture slides, computational MATLAB® and Python resources, and supporting data sets, this is the ideal introduction to digital communications for senior undergraduate and graduate students in electrical engineering.

Cited by 0

Convolutional Codes

William E. Ryan, Shu Lin, Stephen G. Wilson · Cambridge University Press eBooks · 2024

Channel coding lies at the heart of digital communication and data storage. Fully updated, including a new chapter on polar codes, this detailed introduction describes the core theory of channel coding, decoding algorithms, implementation details, and performance analyses. This new edition includes over 50 new end-of-chapter problems and new figures and worked examples throughout. The authors emphasize the practical approach and present clear information on modern channel codes, including turbo and low-density parity-check (LDPC) codes, detailed coverage of BCH codes, Reed-Solomon codes, convolutional codes, finite geometry codes, product codes as well as polar codes for error correction and detection, providing a one-stop resource for 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.

Cited by 0

Convolutional Codes

Julia Lieb, Raquel Pinto, Joachim Rosenthal · arXiv (Cornell University) · 2020

The article provides a survey on convolutional codes stressing the connections to module theory and systems theory. Constructions of codes with maximal possible distance and distance profile are provided. The article will appear as book chapter in "A Concise Encyclopedia of Coding Theory" to be published by CRC Press.

Cited by 0Open access

LDPC convolutional codes based on braided convolutional codes

Marcos B.S. Tavares, Michael Lentmaier, Kamil Sh. Zigangirov et al. · Lund University Publications (Lund University) · 2008

We introduce and analyze new constructions of LDPC convolutional codes and their tail-biting versions which are obtained from braided convolutional codes. The basic ideas behind the encoding and decoding architectures for these codes are presented. Additionally, asymptotic results concerning the iterative thresholds are shown for different ensembles. Finally, we evaluate the bit error rate performances of several codes by means of computer simulations.

Cited by 6Open access

Signal Codes: Convolutional Lattice Codes

Ofir Shalvi, Naftali Sommer, Meir Feder · IEEE Transactions on Information Theory · 2011

The coded modulation scheme proposed in this paper has a simple construction: an integer sequence, representing the information, is convolved with a fixed, continuous-valued, finite impulse response (FIR) filter to generate the codeword - a lattice point. Due to power constraints, the code construction includes a shaping mechanism inspired by precoding techniques such as the Tomlinson-Harashima filter. We naturally term these codes “convolutional lattice codes” or alternatively “signal codes” due to the signal processing interpretation of the code construction. Surprisingly, properly chosen short FIR filters can generate good codes with large minimal distance. Decoding can be done efficiently by sequential decoding or for better performance by bidirectional sequential decoding. Error analysis and simulation results indicate that for the additive white Gaussian noise (AWGN) channel, convolutional lattice codes with computationally reasonable decoders can achieve low error rate close to the channel capacity.

Cited by 45

Recursive convolutional codes for time-invariant LDPC convolutional codes

Éric Roy, Christian Cardinal, David Haccoun · 2010

In this paper we present an attractive alternative to construct time-invariant Low-Density Parity-Check Convolutional Codes (LDPC-CC) of coding rate-b/c from a simple recursive systematic convolutional encoder design. The proposed Recursive Convolutional Doubly-Orthogonal (RCDO) encoders have a corresponding Tanner graph for which the girth is controlled by the doubly-orthogonal conditions that are imposed onto the set of generators that represent the encoder. Therefore, RCDO encoders can be decoded using simply a cascade of the same threshold decoder. The convergence behavior of the iterative decoder is then controlled by the position and by the number of forward and feedback connections that constitute the encoder. RCDO encoders give rise to a class of capacity approaching codes that use simple encoder and decoder structures.

Cited by 4

Hyperimposed convolutional codes

J.-F. Cheng · 2002

New error control codes using superimposed convolutional codes and suboptimal multistage decoding algorithms are proposed. The coding gains of these codes are shown by simulation to be much higher than those of conventional convolutional codes with comparable decoding complexity. The performances of these codes are in fact comparable to turbo codes with soft-output Viterbi decoding but the complexity required is lower.

Cited by 10

Braided convolutional codes

Wei Zhang, Michael Lentmaier, Daniel J. Costello et al. · 2005

We present a new class of iteratively decodable turbo-like codes, called braided convolutional codes. Constructions and encoding procedures for tightly and sparsely braided codes are introduced. Sparsely braided codes exhibit good convergence behavior with iterative decoding, and a statistical analysis using Markov permutors shows that the free distance of these codes grows linearly with constraint length.

Cited by 10

Cascaded convolutional codes

Stefan Höst, Rolf Johannesson, Vladimir Sidorenko et al. · Lund University Publications (Lund University) · 1998

Cited by 6