Asymptotic Reverse-Waterfilling Characterization of Nonanticipative Rate Distortion Function of Vector-Valued Gauss-Markov Processes with MSE Distortion

Photios A. Stavrou; Themistoklis Charalambous; Charalambos D. Charalambous; Sergey Loyka; Mikael Skoglund

doi:10.1109/CDC.2018.8619725

Asymptotic Reverse-Waterfilling Characterization of Nonanticipative Rate Distortion Function of Vector-Valued Gauss-Markov Processes with MSE Distortion

Photios A. Stavrou, Themistoklis Charalambous, Charalambos D. Charalambous, Sergey Loyka, Mikael Skoglund

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

3 Citations (Scopus)

241 Downloads (Pure)

Abstract

We analyze the asymptotic nonanticipative rate distortion function (NRDF) of vector-valued Gauss-Markov processes subject to a mean-squared error (MSE) distortion function. We derive a parametric characterization in terms of a reverse-waterfilling algorithm, that requires the solution of a matrix Riccati algebraic equation (RAE). Further, we develop an algorithm reminiscent of the classical reverse-waterfilling algorithm that provides an upper bound to the optimal solution of the reverse-waterfilling optimization problem, and under certain cases, it operates at the NRDF. Moreover, using the characterization of the reverse-waterfilling algorithm, we derive the analytical solution of the NRDF, for a simple two-dimensional parallel Gauss-Markov process. The efficacy of our proposed algorithm is demonstrated via an example.

Original language	English
Title of host publication	Proceedings of 57th IEEE Conference on Decision and Control, CDC 2018
Publisher	IEEE
Pages	14-20
Number of pages	7
ISBN (Electronic)	9781538613955
DOIs	https://doi.org/10.1109/CDC.2018.8619725
Publication status	Published - 18 Jan 2019
MoE publication type	A4 Conference publication
Event	IEEE Conference on Decision and Control - Miami, United States Duration: 17 Dec 2018 → 19 Dec 2018 Conference number: 57

Publication series

Name	Proceedings of the IEEE Conference on Decision & Control
ISSN (Print)	0743-1546

Conference

Conference	IEEE Conference on Decision and Control
Abbreviated title	CDC
Country/Territory	United States
City	Miami
Period	17/12/2018 → 19/12/2018

Keywords

distortion
RNA
symmetric matrices
rate-distortion
resource description framework
entropy
optimization

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10.1109/CDC.2018.8619725

ELEC_Stavrou_etal_Asymtotic-Reverse-Waterfilling_CDC2018Final published version, 269 KB

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Stavrou, P. A., Charalambous, T., Charalambous, C. D., Loyka, S., & Skoglund, M. (2019). Asymptotic Reverse-Waterfilling Characterization of Nonanticipative Rate Distortion Function of Vector-Valued Gauss-Markov Processes with MSE Distortion. In Proceedings of 57th IEEE Conference on Decision and Control, CDC 2018 (pp. 14-20). Article 8619725 (Proceedings of the IEEE Conference on Decision & Control). IEEE. https://doi.org/10.1109/CDC.2018.8619725

Stavrou, Photios A. ; Charalambous, Themistoklis ; Charalambous, Charalambos D. et al. / Asymptotic Reverse-Waterfilling Characterization of Nonanticipative Rate Distortion Function of Vector-Valued Gauss-Markov Processes with MSE Distortion. Proceedings of 57th IEEE Conference on Decision and Control, CDC 2018. IEEE, 2019. pp. 14-20 (Proceedings of the IEEE Conference on Decision & Control).

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title = "Asymptotic Reverse-Waterfilling Characterization of Nonanticipative Rate Distortion Function of Vector-Valued Gauss-Markov Processes with MSE Distortion",

abstract = "We analyze the asymptotic nonanticipative rate distortion function (NRDF) of vector-valued Gauss-Markov processes subject to a mean-squared error (MSE) distortion function. We derive a parametric characterization in terms of a reverse-waterfilling algorithm, that requires the solution of a matrix Riccati algebraic equation (RAE). Further, we develop an algorithm reminiscent of the classical reverse-waterfilling algorithm that provides an upper bound to the optimal solution of the reverse-waterfilling optimization problem, and under certain cases, it operates at the NRDF. Moreover, using the characterization of the reverse-waterfilling algorithm, we derive the analytical solution of the NRDF, for a simple two-dimensional parallel Gauss-Markov process. The efficacy of our proposed algorithm is demonstrated via an example.",

keywords = "distortion, RNA, symmetric matrices, rate-distortion, resource description framework, entropy, optimization",

author = "Stavrou, {Photios A.} and Themistoklis Charalambous and Charalambous, {Charalambos D.} and Sergey Loyka and Mikael Skoglund",

year = "2019",

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doi = "10.1109/CDC.2018.8619725",

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publisher = "IEEE",

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Stavrou, PA, Charalambous, T, Charalambous, CD, Loyka, S & Skoglund, M 2019, Asymptotic Reverse-Waterfilling Characterization of Nonanticipative Rate Distortion Function of Vector-Valued Gauss-Markov Processes with MSE Distortion. in Proceedings of 57th IEEE Conference on Decision and Control, CDC 2018., 8619725, Proceedings of the IEEE Conference on Decision & Control, IEEE, pp. 14-20, IEEE Conference on Decision and Control, Miami, Florida, United States, 17/12/2018. https://doi.org/10.1109/CDC.2018.8619725

Asymptotic Reverse-Waterfilling Characterization of Nonanticipative Rate Distortion Function of Vector-Valued Gauss-Markov Processes with MSE Distortion. / Stavrou, Photios A.; Charalambous, Themistoklis; Charalambous, Charalambos D. et al.
Proceedings of 57th IEEE Conference on Decision and Control, CDC 2018. IEEE, 2019. p. 14-20 8619725 (Proceedings of the IEEE Conference on Decision & Control).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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AU - Stavrou, Photios A.

AU - Charalambous, Themistoklis

AU - Charalambous, Charalambos D.

AU - Loyka, Sergey

AU - Skoglund, Mikael

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N2 - We analyze the asymptotic nonanticipative rate distortion function (NRDF) of vector-valued Gauss-Markov processes subject to a mean-squared error (MSE) distortion function. We derive a parametric characterization in terms of a reverse-waterfilling algorithm, that requires the solution of a matrix Riccati algebraic equation (RAE). Further, we develop an algorithm reminiscent of the classical reverse-waterfilling algorithm that provides an upper bound to the optimal solution of the reverse-waterfilling optimization problem, and under certain cases, it operates at the NRDF. Moreover, using the characterization of the reverse-waterfilling algorithm, we derive the analytical solution of the NRDF, for a simple two-dimensional parallel Gauss-Markov process. The efficacy of our proposed algorithm is demonstrated via an example.

AB - We analyze the asymptotic nonanticipative rate distortion function (NRDF) of vector-valued Gauss-Markov processes subject to a mean-squared error (MSE) distortion function. We derive a parametric characterization in terms of a reverse-waterfilling algorithm, that requires the solution of a matrix Riccati algebraic equation (RAE). Further, we develop an algorithm reminiscent of the classical reverse-waterfilling algorithm that provides an upper bound to the optimal solution of the reverse-waterfilling optimization problem, and under certain cases, it operates at the NRDF. Moreover, using the characterization of the reverse-waterfilling algorithm, we derive the analytical solution of the NRDF, for a simple two-dimensional parallel Gauss-Markov process. The efficacy of our proposed algorithm is demonstrated via an example.

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Stavrou PA, Charalambous T, Charalambous CD, Loyka S, Skoglund M. Asymptotic Reverse-Waterfilling Characterization of Nonanticipative Rate Distortion Function of Vector-Valued Gauss-Markov Processes with MSE Distortion. In Proceedings of 57th IEEE Conference on Decision and Control, CDC 2018. IEEE. 2019. p. 14-20. 8619725. (Proceedings of the IEEE Conference on Decision & Control). doi: 10.1109/CDC.2018.8619725

Asymptotic Reverse-Waterfilling Characterization of Nonanticipative Rate Distortion Function of Vector-Valued Gauss-Markov Processes with MSE Distortion

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