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http://hdl.handle.net/10773/36225
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DC Field | Value | Language |
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dc.contributor.author | Pinto, Raquel | pt_PT |
dc.contributor.author | Vela, Carlos | pt_PT |
dc.date.accessioned | 2023-02-03T19:42:53Z | - |
dc.date.available | 2023-02-03T19:42:53Z | - |
dc.date.issued | 2022-10-07 | - |
dc.identifier.uri | http://hdl.handle.net/10773/36225 | - |
dc.description.abstract | Network coding theory provides a pragmatic instrument to disseminate information (packets) over networks where there may be many information sources and possibly many receivers. From a mathematical point of view, these packets can be modelled by columns of matrices over a finite field Fq and during the transmission, these columns are linearly combined at each node of the network. To achieve reliable communication over this channel, rank-metric codes are typically employed. Nevertheless, network coding techniques for streaming are fundamentally different from the classical ones. To be optimised they must operate under low-latency, sequential encoding and decoding constraints, and as such they must inherently have a convolutional structure. That is the reason why most of the proposed schemes for this scenario employ convolutional codes in different ways. | pt_PT |
dc.language.iso | eng | pt_PT |
dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04106%2F2020/PT | pt_PT |
dc.rights | openAccess | pt_PT |
dc.subject | Rank-metric codes | pt_PT |
dc.subject | Optimal | pt_PT |
dc.subject | Rank-deficiency channel | pt_PT |
dc.subject | Decoding method | pt_PT |
dc.title | Maximum rank distance profile codes | pt_PT |
dc.type | conferenceObject | pt_PT |
dc.description.version | Not Published | pt_PT |
dc.peerreviewed | yes | pt_PT |
ua.event.date | 5-7 Outubro, 2022 | pt_PT |
degois.publication.title | 8th Iberian Mathematical Meeting | pt_PT |
Appears in Collections: | DMat - Comunicações |
Files in This Item:
File | Description | Size | Format | |
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8IMM_Poster.pdf | 5.56 MB | Adobe PDF | View/Open |
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