### Abstract

Original language | English |
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Book series | Lecture Notes in Computer Science |

Volume | 6827 |

Pages (from-to) | 129-137 |

Number of pages | 8 |

ISSN | 0302-9743 |

DOIs | |

Publication status | Published - 13 May 2011 |

Event | Networking 2011, NC-Pro - Valencia, Spain Duration: 13 May 2011 → 13 May 2011 |

### Workshop

Workshop | Networking 2011, NC-Pro |
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Country | Spain |

City | Valencia |

Period | 13/05/2011 → 13/05/2011 |

### Fingerprint

### Cite this

*Lecture Notes in Computer Science*,

*6827*, 129-137. https://doi.org/10.1007/978-3-642-23041-7_13

}

*Lecture Notes in Computer Science*, vol. 6827, pp. 129-137. https://doi.org/10.1007/978-3-642-23041-7_13

**Decoding Algorithms for Random Linear Network Codes.** / Heide, Janus; Pedersen, Morten Videbæk; Fitzek, Frank.

Research output: Contribution to journal › Conference article in Journal › Research › peer-review

TY - GEN

T1 - Decoding Algorithms for Random Linear Network Codes

AU - Heide, Janus

AU - Pedersen, Morten Videbæk

AU - Fitzek, Frank

N1 - International IFIP TC 6 Workshops, PE-CRN, NC-Pro, WCNS, and SUNSET 2011, Held at NETWORKING 2011, Valencia, Spain, May 13, 2011. (eds.) Casares-Giner, Vincente, Manzoni, Pietro & Pont, Ana.

PY - 2011/5/13

Y1 - 2011/5/13

N2 - We consider the problem of efficient decoding of a random linear code over a finite field. In particular we are interested in the case where the code is random, relatively sparse, and use the binary finite field as an example. The goal is to decode the data using fewer operations to potentially achieve a high coding throughput, and reduce energy consumption.We use an on-the-fly version of the Gauss-Jordan algorithm as a baseline, and provide several simple improvements to reduce the number of operations needed to perform decoding. Our tests show that the improvements can reduce the number of operations used during decoding with 10-20% on average depending on the code parameters.

AB - We consider the problem of efficient decoding of a random linear code over a finite field. In particular we are interested in the case where the code is random, relatively sparse, and use the binary finite field as an example. The goal is to decode the data using fewer operations to potentially achieve a high coding throughput, and reduce energy consumption.We use an on-the-fly version of the Gauss-Jordan algorithm as a baseline, and provide several simple improvements to reduce the number of operations needed to perform decoding. Our tests show that the improvements can reduce the number of operations used during decoding with 10-20% on average depending on the code parameters.

U2 - 10.1007/978-3-642-23041-7_13

DO - 10.1007/978-3-642-23041-7_13

M3 - Conference article in Journal

VL - 6827

SP - 129

EP - 137

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

SN - 0302-9743

ER -