2016IEEE Transactions on Information TheoryRequires access

Construction of Partial-Unit-Memory MDS Convolutional Codes

Chin Hei Chan, Maosheng Xiong

Open publisher page 3 citations

Abstract

Maximum-distance separable (MDS) convolutional codes form an optimal family of convolutional codes, the study of which is of great importance. There are very few general algebraic constructions of MDS convolutional codes. In this paper, we construct a large family of partial-unit-memory MDS convolutional codes over Fqwith flexible parameters. Compared with the previous work, the field size q required to define these codes is much smaller. The construction also leads to many new strongly MDS convolutional codes, an important subclass of MDS convolutional codes. Some examples are presented at the end of this paper.

About this research paper

What this paper is about

Maximum-distance separable (MDS) convolutional codes form an optimal family of convolutional codes, the study of which is of great importance. There are very few general algebraic constructions of MDS convolutional codes. In this paper, we construct a large family of partial-unit-memory MDS convolutional codes over Fqwith flexible parameters. Compared with the previous work, the field size q required to define these codes is much smaller. The construction also leads to many new strongly MDS convolutional codes, an important subclass of MDS convolutional codes. Some examples are presented at the end of this paper.

Why it matters

OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Maximum-distance separable (MDS) convolutional codes form an optimal family of convolutional codes, the study of which is of great importance. There are very few general algebraic constructions of MDS convolutional codes. In this paper, we construct a large family of partial-unit-memory MDS convolutional codes over Fqwith flexible parameters. Compared with the previous work, the field size q required to define these codes is much smaller. The construction also leads to many new strongly MDS convolutional codes, an important subclass of MDS convolutional codes. Some examples are presented at the end of this paper.

Key concepts: Convolutional code, Separable space, Finite field, Serial concatenated convolutional codes, Linear code, Computer science, Turbo code, Quantum convolutional code

Related papers

Back to paper searchBrowse research topicsOriginal source
Construction of Partial-Unit-Memory MDS Convolutional Codes — Research Paper | ScholarLens