000188543 001__ 188543
000188543 005__ 20190617200704.0
000188543 022__ $$a0090-6778
000188543 037__ $$aARTICLE
000188543 245__ $$aReconstruction of Network Coded Sources From Incomplete Datasets
000188543 260__ $$bInstitute of Electrical and Electronics Engineers$$c2015
000188543 269__ $$a2015
000188543 336__ $$aJournal Articles
000188543 520__ $$aWe investigate the problem of recovering source information from an incomplete set of network coded data with help of prior information about the sources. This problem naturally arises in wireless networks, where the number of network coded packets available at the receiver may not be sufficient for exact decoding due to channel dynamics or timing constraints, for example. We study the theoretical performance of such systems under maximum a posteriori (MAP) decoding and examine the influence of the data priors and in particular source correlation on the decoding performance. We also propose a low complexity iterative decoding algorithm based on message passing for decoding the network coded data in the case of pairwise linearly correlated source data. Our algorithm operates on a graph that captures the network coding constraints, while the knowledge about the source correlation is directly incorporated in the messages exchanged over the graph. We test the proposed method on both synthetic data and correlated image sequences and demonstrate that the prior knowledge about the statistical properties of the sources can be effectively exploited at the decoder in order to provide a good reconstruction of the transmitted data.
000188543 6531_ $$aNetwork coding
000188543 6531_ $$acorrelated sources
000188543 6531_ $$amessage passing
000188543 6531_ $$afactor graph
000188543 700__ $$0242950$$g183797$$aBourtsoulatze, Eirina
000188543 700__ $$0(EPFLAUTH)176186$$g176186$$aThomos, Nikolaos
000188543 700__ $$aFrossard, Pascal$$g101475$$0241061
000188543 773__ $$tIEEE Transactions on Communications
000188543 8564_ $$uhttp://arxiv.org/abs/1307.7138$$zURL
000188543 909C0 $$xU10851$$0252393$$pLTS4
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000188543 917Z8 $$x176186
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000188543 937__ $$aEPFL-ARTICLE-188543
000188543 973__ $$rREVIEWED$$sSUBMITTED$$aEPFL
000188543 980__ $$aARTICLE