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https://dx.doi.org/10.48550/ar...
Article . 2015
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Riemann-Roch Spaces and Linear Network Codes

Authors: Hansen, Johan P.;

Riemann-Roch Spaces and Linear Network Codes

Abstract

We construct linear network codes utilizing algebraic curves over finite fields and certain associated Riemann-Roch spaces and present methods to obtain their parameters. In particular we treat the Hermitian curve and the curves associated with the Suzuki and Ree groups all having the maximal number of points for curves of their respective genera. Linear network coding transmits information in terms of a basis of a vector space and the information is received as a basis of a possibly altered vector space. Ralf Koetter and Frank R. Kschischang %\cite{DBLP:journals/tit/KoetterK08} introduced a metric on the set of vector spaces and showed that a minimal distance decoder for this metric achieves correct decoding if the dimension of the intersection of the transmitted and received vector space is sufficiently large. The vector spaces in our construction have minimal distance bounded from below in the above metric making them suitable for linear network coding.

8 pages

Country
Denmark
Related Organizations
Keywords

FOS: Computer and information sciences, Computer Science - Information Theory, Information Theory (cs.IT), cs.IT, 68M10, 90B18, 94A05, math.IT

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citations
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!
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