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conference paper

On the dependency between the code symmetries and the decoding efficiency

Ivanov, Kirill  
•
Urbanke, Ruediger  
January 1, 2020
Proceedings Of 2020 International Symposium On Information Theory And Its Applications (Isita2020)
International Symposium on Information Theory and its Applications (ISITA)

A framework of monomial codes is considered, which includes linear codes generated by the evaluation of certain monomials. Polar and Reed-Muller codes are the two best-known representatives of such codes and can be considered as two extreme cases. Reed-Muller codes have a large automorphism group but their low-complexity maximum likelihood decoding still remains an open problem. On the other hand, polar codes have much less symmetries but admit the efficient near-ML decoding.

We study the dependency between the code symmetries and the decoding efficiency. We introduce a new family of codes, partially symmetric monomial codes. These codes have a smaller group of symmetries than the Reed-Muller codes and are in this sense "between" RM and polar codes. A lower bound on their parameters is introduced along with the explicit construction which achieves it. Structural properties of these codes are demonstrated and it is shown that they often have a recursive structure.

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Type
conference paper
Web of Science ID

WOS:000714960300040

Author(s)
Ivanov, Kirill  
Urbanke, Ruediger  
Date Issued

2020-01-01

Publisher

IEEE

Publisher place

New York

Published in
Proceedings Of 2020 International Symposium On Information Theory And Its Applications (Isita2020)
ISBN of the book

978-4-88552-330-4

Series title/Series vol.

International Symposium on Information Theory and its Applications

Start page

195

End page

199

Subjects

Computer Science, Information Systems

•

Computer Science, Theory & Methods

•

Computer Science

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LTHC  
Event nameEvent placeEvent date
International Symposium on Information Theory and its Applications (ISITA)

ELECTR NETWORK

Oct 24-27, 2020

Available on Infoscience
December 18, 2021
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/183838
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