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dc.contributor.authorPinto, Raquelpt_PT
dc.contributor.authorVela, Carlospt_PT
dc.description.abstractNetwork 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.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04106%2F2020/PTpt_PT
dc.subjectRank-metric codespt_PT
dc.subjectRank-deficiency channelpt_PT
dc.subjectDecoding methodpt_PT
dc.titleMaximum rank distance profile codespt_PT
dc.description.versionNot Publishedpt_PT
ua.event.date5-7 Outubro, 2022pt_PT
degois.publication.title8th Iberian Mathematical Meetingpt_PT
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