The Rank Distribution of Sparse Random Linear Network Coding

Sparse random linear network coding (SRLNC) is a promising solution for reducing the complexity of random linear network coding (RLNC). RLNC can be modeled as a linear operator channel (LOC). It is well known that the normalized channel capacity of LOC is characterized by the rank distribution of th...

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Bibliographic Details
Published in:	IEEE access Vol. 7; pp. 43806 - 43819
Main Authors:	Chen, Wenlin, Lu, Fang, Dong, Yan
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Approximation Channel capacity Coding Complexity theory Decoding Encoding Fields (mathematics) Linear operators Mathematical analysis Network coding Operators (mathematics) Probability Rank distribution Sparse matrices sparse random linear network coding Sparsity Transfer matrices
ISSN:	2169-3536, 2169-3536
Online Access:	Get full text
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