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      Distributed Remote Vector Gaussian Source Coding for Wireless Acoustic Sensor Networks

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          Abstract

          In this paper, we consider the problem of remote vector Gaussian source coding for a wireless acoustic sensor network. Each node receives messages from multiple nodes in the network and decodes these messages using its own measurement of the sound field as side information. The node's measurement and the estimates of the source resulting from decoding the received messages are then jointly encoded and transmitted to a neighboring node in the network. We show that for this distributed source coding scenario, one can encode a so-called conditional sufficient statistic of the sources instead of jointly encoding multiple sources. We focus on the case where node measurements are in form of noisy linearly mixed combinations of the sources and the acoustic channel mixing matrices are invertible. For this problem, we derive the rate-distortion function for vector Gaussian sources and under covariance distortion constraints.

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          Author and article information

          Journal
          2014-01-16
          Article
          1401.3945
          d1f5ddf2-8804-49dd-a10e-c7f728b9a841

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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          Custom metadata
          10 pages, to be presented at the IEEE DCC'14
          cs.IT math.IT

          Numerical methods,Information systems & theory
          Numerical methods, Information systems & theory

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