A convolutional code can be decomposed into smaller codes if it admits decoupled encoders. In this paper, we show that if a code can be decomposed into smaller codes (subcodes) its column distances are the minimum of the column distances of its subcodes. Moreover, the j-th column distance of a convolutional code C is equal to the j-th column distance of the convolutional codes generated by the truncation of the canonical encoders of C to matrices which entries have degree smaller or equal than j. We show that if one of such codes can be decomposed into smaller codes, so can be all the other codes. Key words: Convolutional codes, decoupled encoders, code decomposition, free distance, column distance AMS subject classifications:
In this paper we present the analytical results of the computational requirement for the minimum-dis...
Convolutional codes are characterized by a trellis structure. Maximum-likelihood decoding is charact...
Fundamentals of Convolutional Coding, Second Edition, regarded as a bible of convolutional coding br...
A convolutional code can be decomposed into smaller codes if it admits decoupled encoders. In this p...
The minimum distance of a code is an important measure of robustness of the code since it provides a...
A maximum distance separable (MDS) block code is a linear code whose distance is maximal among all l...
Rate 1/2 binary convolutional codes are analyzed and a lower bound on free distance in terms of the ...
We discuss about construction of convolutional codes via linear system approach. The main discussion...
Many communication systems obtain enhanced performance by using concatenated coding schemes. Turbo c...
Nested convolutional codes are a set of convolutional codes that is derived from a given generator m...
AbstractIn this paper, we characterize four models of concatenation of a block code and a convolutio...
Abstract—A new module structure for convolutional codes is in-troduced and used to establish further...
A lower bound on the free distance of LDPC convolutional codes defined by syndrome former matrices c...
AbstractThis article focuses on the characterization of two models of concatenated convolutional cod...
AbstractIn this paper, polynomial matrix fraction descriptions (MFDs) are used as a tool for investi...
In this paper we present the analytical results of the computational requirement for the minimum-dis...
Convolutional codes are characterized by a trellis structure. Maximum-likelihood decoding is charact...
Fundamentals of Convolutional Coding, Second Edition, regarded as a bible of convolutional coding br...
A convolutional code can be decomposed into smaller codes if it admits decoupled encoders. In this p...
The minimum distance of a code is an important measure of robustness of the code since it provides a...
A maximum distance separable (MDS) block code is a linear code whose distance is maximal among all l...
Rate 1/2 binary convolutional codes are analyzed and a lower bound on free distance in terms of the ...
We discuss about construction of convolutional codes via linear system approach. The main discussion...
Many communication systems obtain enhanced performance by using concatenated coding schemes. Turbo c...
Nested convolutional codes are a set of convolutional codes that is derived from a given generator m...
AbstractIn this paper, we characterize four models of concatenation of a block code and a convolutio...
Abstract—A new module structure for convolutional codes is in-troduced and used to establish further...
A lower bound on the free distance of LDPC convolutional codes defined by syndrome former matrices c...
AbstractThis article focuses on the characterization of two models of concatenated convolutional cod...
AbstractIn this paper, polynomial matrix fraction descriptions (MFDs) are used as a tool for investi...
In this paper we present the analytical results of the computational requirement for the minimum-dis...
Convolutional codes are characterized by a trellis structure. Maximum-likelihood decoding is charact...
Fundamentals of Convolutional Coding, Second Edition, regarded as a bible of convolutional coding br...