Decoding Algorithms for Random Linear Network Codes

Janus Heide, Morten Videbæk Pedersen, Frank Fitzek

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9 Citationer (Scopus)
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Resumé

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.
OriginalsprogEngelsk
BogserieLecture Notes in Computer Science
Vol/bind6827
Sider (fra-til)129-137
Antal sider8
ISSN0302-9743
DOI
StatusUdgivet - 13 maj 2011
BegivenhedNetworking 2011, NC-Pro - Valencia, Spanien
Varighed: 13 maj 201113 maj 2011

Workshop

WorkshopNetworking 2011, NC-Pro
LandSpanien
ByValencia
Periode13/05/201113/05/2011

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Linear networks
Decoding
Galois field
Decode
Linear Codes
Gauss
Energy Consumption
Baseline
Throughput
Energy utilization
Coding
Binary

Bibliografisk note

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.

Citer dette

Heide, Janus ; Pedersen, Morten Videbæk ; Fitzek, Frank. / Decoding Algorithms for Random Linear Network Codes. I: Lecture Notes in Computer Science. 2011 ; Bind 6827. s. 129-137.
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Decoding Algorithms for Random Linear Network Codes. / Heide, Janus; Pedersen, Morten Videbæk; Fitzek, Frank.

I: Lecture Notes in Computer Science, Bind 6827, 13.05.2011, s. 129-137.

Publikation: Bidrag til tidsskriftKonferenceartikel i tidsskriftForskningpeer review

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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.

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