A Generator-Matrix-Based Approach for Adaptively Generating Cut-Inducing Redundant Parity Checks

Hossein Falsafain, Seyed Rasoul Mousavi

Research output: Contribution to journalArticle

Abstract

A generator matrix (GM)-based approach for adaptively deriving cut-inducing redundant parity checks (RPCs) during the adaptive linear programming decoding algorithm is presented. More precisely speaking, if the decoder gets stuck in a non-integral pseudocodeword, then the resulting RPCs are likely to provide violated forbidden-set inequalities that can separate this non-integral optimal solution from the feasible region. The described approach can be viewed as a GM-based counterpart of the approach proposed by Zhang and Siegel in 2012. For binary linear codes of low rate, while providing the same error-correcting performance, our approach requires much less computational time compared to its analogue.
Original languageEnglish
Pages (from-to)640-643
Number of pages4
JournalIEEE Communications Letters
Volume20
Issue number4
DOIs
Publication statusPublished - 16 Feb 2016

Fingerprint

Linear programming
Decoding

Cite this

A Generator-Matrix-Based Approach for Adaptively Generating Cut-Inducing Redundant Parity Checks. / Falsafain, Hossein; Mousavi, Seyed Rasoul.

In: IEEE Communications Letters, Vol. 20, No. 4, 16.02.2016, p. 640-643.

Research output: Contribution to journalArticle

Falsafain, Hossein ; Mousavi, Seyed Rasoul. / A Generator-Matrix-Based Approach for Adaptively Generating Cut-Inducing Redundant Parity Checks. In: IEEE Communications Letters. 2016 ; Vol. 20, No. 4. pp. 640-643.
@article{9d74593a802e4f78bb1f81ccbf87effc,
title = "A Generator-Matrix-Based Approach for Adaptively Generating Cut-Inducing Redundant Parity Checks",
abstract = "A generator matrix (GM)-based approach for adaptively deriving cut-inducing redundant parity checks (RPCs) during the adaptive linear programming decoding algorithm is presented. More precisely speaking, if the decoder gets stuck in a non-integral pseudocodeword, then the resulting RPCs are likely to provide violated forbidden-set inequalities that can separate this non-integral optimal solution from the feasible region. The described approach can be viewed as a GM-based counterpart of the approach proposed by Zhang and Siegel in 2012. For binary linear codes of low rate, while providing the same error-correcting performance, our approach requires much less computational time compared to its analogue.",
author = "Hossein Falsafain and Mousavi, {Seyed Rasoul}",
year = "2016",
month = "2",
day = "16",
doi = "10.1109/LCOMM.2016.2530706",
language = "English",
volume = "20",
pages = "640--643",
journal = "IEEE Communications Letters",
issn = "1089-7798",
publisher = "Institute of Electrical and Electronics Engineers",
number = "4",

}

TY - JOUR

T1 - A Generator-Matrix-Based Approach for Adaptively Generating Cut-Inducing Redundant Parity Checks

AU - Falsafain, Hossein

AU - Mousavi, Seyed Rasoul

PY - 2016/2/16

Y1 - 2016/2/16

N2 - A generator matrix (GM)-based approach for adaptively deriving cut-inducing redundant parity checks (RPCs) during the adaptive linear programming decoding algorithm is presented. More precisely speaking, if the decoder gets stuck in a non-integral pseudocodeword, then the resulting RPCs are likely to provide violated forbidden-set inequalities that can separate this non-integral optimal solution from the feasible region. The described approach can be viewed as a GM-based counterpart of the approach proposed by Zhang and Siegel in 2012. For binary linear codes of low rate, while providing the same error-correcting performance, our approach requires much less computational time compared to its analogue.

AB - A generator matrix (GM)-based approach for adaptively deriving cut-inducing redundant parity checks (RPCs) during the adaptive linear programming decoding algorithm is presented. More precisely speaking, if the decoder gets stuck in a non-integral pseudocodeword, then the resulting RPCs are likely to provide violated forbidden-set inequalities that can separate this non-integral optimal solution from the feasible region. The described approach can be viewed as a GM-based counterpart of the approach proposed by Zhang and Siegel in 2012. For binary linear codes of low rate, while providing the same error-correcting performance, our approach requires much less computational time compared to its analogue.

U2 - 10.1109/LCOMM.2016.2530706

DO - 10.1109/LCOMM.2016.2530706

M3 - Article

VL - 20

SP - 640

EP - 643

JO - IEEE Communications Letters

JF - IEEE Communications Letters

SN - 1089-7798

IS - 4

ER -