Semidefinite Programming Approach to Gaussian Sequential Rate-Distortion Trade-offs
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1411.7632.pdf
Description
Accepted version
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1.35 MB
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Adobe PDF
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452670e656061e36f2ba32ff9bc05569
Author(s)
Tanaka, Takashi
Baek, Kwang Ki
Parrilo, Pablo A.
Mitter, Sanjoy K
Date Issued
April 2017
Journal
IEEE Transactions on Automatic Control
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Tanaka, Takashi, Kwang-Ki K. Kim, Pablo A. Parrilo and Sanjoy K. Mitter. "Semidefinite Programming Approach to Gaussian Sequential Rate-Distortion Trade-offs." IEEE Transactions on Automatic Control 62, Issue: 4 (April 2017).
Version
Author's final manuscript
Abstract
Sequential rate-distortion (SRD) theory provides a framework for studying the fundamental trade-off between data-rate and data-quality in real-time communication systems. In this paper, we consider the SRD problem for multi-dimensional time-varying Gauss-Markov processes under mean-square distortion criteria. We first revisit the sensor-estimator separation principle, which asserts that considered SRD problem is equivalent to a joint sensor and estimator design problem in which data-rate of the sensor output is minimized while the estimator's performance satisfies the distortion criteria. We then show that the optimal joint design can be performed by semidefinite programming. A semidefinite representation of the corresponding SRD function is obtained. Implications of the obtained result in the context of zero-delay source coding theory and applications to networked control theory are also discussed.
MIT Department
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
Massachusetts Institute of Technology. Department of Materials Science and Engineering
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1109/TAC.2016.2601148
