inC OMPUTER SCIENCE AND AUTOMATION

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Název: inC OMPUTER SCIENCE AND AUTOMATION
Autoři: On Tailbiting Trellises, K Sasidharan
Přispěvatelé: The Pennsylvania State University CiteSeerX Archives
Zdroj: http://drona.csa.iisc.ernet.in/~priti/sasi.ps.
Rok vydání: 2000
Sbírka: CiteSeerX
Popis: Tail-biting trellises for block codes have considerably fewer number of states than conventional trellises and hence have potential for greatly improving the decoder performance. Although the formal theory for constructing such trellises is currently being worked out, a few tail-biting trellises for some linear block codes are available. Minimal tail-biting trellis for (15,11) Reed Solomon code which belongs to a class of codes known as Maximum Distance Seperable(MDS) codes has been constructed based upon existing theorem. An efficient maximum likelihood soft-decision decoding algorithm for tail-biting trellises is proposed. Experiments indicate that the decoding algorithm is considerably more efficient than the traditional Viterbi algorithm run on the conventional trellis.
Druh dokumentu: text
Popis souboru: application/postscript
Jazyk: English
Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.124.5694; http://drona.csa.iisc.ernet.in/~priti/sasi.ps
Dostupnost: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.124.5694
http://drona.csa.iisc.ernet.in/~priti/sasi.ps
Rights: Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Přístupové číslo: edsbas.8A1C4897
Databáze: BASE
Popis
Abstrakt:Tail-biting trellises for block codes have considerably fewer number of states than conventional trellises and hence have potential for greatly improving the decoder performance. Although the formal theory for constructing such trellises is currently being worked out, a few tail-biting trellises for some linear block codes are available. Minimal tail-biting trellis for (15,11) Reed Solomon code which belongs to a class of codes known as Maximum Distance Seperable(MDS) codes has been constructed based upon existing theorem. An efficient maximum likelihood soft-decision decoding algorithm for tail-biting trellises is proposed. Experiments indicate that the decoding algorithm is considerably more efficient than the traditional Viterbi algorithm run on the conventional trellis.