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Computer Communications
Article . 2023 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2022
License: CC BY NC ND
Data sources: Datacite
DBLP
Article . 2022
Data sources: DBLP
DBLP
Article . 2023
Data sources: DBLP
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Sub-rate linear network coding

Authors: Ben Grinboim; Itay Shrem; Ofer Amrani;

Sub-rate linear network coding

Abstract

Increasing network utilization is often considered as the holy grail of communications. In this article, the concept of sub-rate coding and decoding in the framework of linear network coding (LNC) is discussed for single-source multiple-sinks finite acyclic networks. Sub-rate coding offers an add-on to existing LNC. It allows sinks whose max-flow is smaller than the source message-rate, termed \emph{sub-rate sinks}, to decode a portion of the transmitted message without degrading the maximum achievable rate of LNC sinks whose max-flow is equal (or greater) than the rate of the source node. The article studies theoretical aspects of sub-rate coding by formulating the conditions a node (and indeed the network) must fulfill so as to qualify as a legitimate sub-rate sink.

Keywords

Signal Processing (eess.SP), FOS: Computer and information sciences, Computer Science - Information Theory, Information Theory (cs.IT), FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Signal Processing

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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!
0
Average
Average
Average
Green