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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Microprocessors and ...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Microprocessors and Microsystems
Article . 2012 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
DBLP
Article . 2012
Data sources: DBLP
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Decoding of Raptor codes on embedded systems

Authors: Todor Mladenov; Saeid Nooshabadi; Juan A. Montiel-Nelson; Keseon Kim;

Decoding of Raptor codes on embedded systems

Abstract

Raptor codes have been proven very suitable for mobile multimedia content delivery. A systematic Raptor code is employed for the application layer Forward Error Correction (FEC), schemes of the 3rd Generation Partnership Project (3GPP), Multimedia Broadcast/Multicast Service (MBMS) and standard and the IP Datacast over Digital Video Broadcasting (DVB) services. Those services run on mobile devices powered by embedded systems. This paper analyzes the performance, energy profile and resource implication of Raptor decoder on a system on a chip (SoC) platform with a soft-core embedded processor. At the heart of the Raptor decoder for binary erasure channel (BEC) is the decoding of the pre-code. The following three methods are used for that task: Belief Propagation (BP), Gaussian Elimination (GE) and the 3GPP inactivation decoding Gaussian elimination (IDGE). The paper analyzes the error correction capability and the complexity of each algorithm on embedded system. Additionally, the paper investigates how the cache size, matrix memory type and organization affect the algorithms under consideration. Finally, a power and energy dissipation analysis for the operation of the three algorithms under consideration is presented.

0,218

0,549

SCIE

382

375

Q3

Keywords

3307 Tecnología electrónica, Gaussian elimination, Belief propagation, Raptor code, Embedded system, Inactivation decoding

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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