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Abstract: We consider the distributed source coding problem in which correlated datapicked up by scattered sensors has to be encoded separately and transmitted toa common receiver, subject to a rate-distortion constraint. Althoughnear-tooptimal solutions based on Turbo and LDPC codes exist for this problem,in most cases the proposed techniques do not scale to networks of hundreds ofsensors. We present a scalable solution based on the following key elements:a distortion-optimized index assignments for low-complexity distributedquantization, b source-optimized hierarchical clustering based on theKullback-Leibler distance and c sum-product decoding on specific factorgraphs exploiting the correlation of the data.



Autor: G. Maierbacher, J. Barros

Fuente: https://arxiv.org/



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