Closed-form MSE performance of the distributed LMS algorithm

Gonzalo Mateos; Ioannis D. Schizas; Georgios B. Giannakis

doi:10.1109/DSP.2009.4785897

Closed-form MSE performance of the distributed LMS algorithm

Gonzalo Mateos
, Ioannis D. Schizas
, Georgios B. Giannakis

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Scopus citations

Abstract

Mean-square error (MSE) performance analysis is conducted for a novel distributed least-mean square (D-LMS) algorithm, which is based on consensus, in-network, adaptive estimation using wireless sensor networks (WSNs). For sensor observations that are linearly related to the time-invariant parameter of interest and independent Gaussian data, exact closed-form expressions are derived for the global and sensor-level MSE evolution and steady-state limiting values. Tracking performance is also investigated when the true parameter adheres to a random-walk model. Remarkably, for small step-sizes the results accurately extend to the pragmatic setup whereby sensors acquire temporally-correlated (non-)Gaussian data.

Original language	English (US)
Title of host publication	2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009, Proceedings
Pages	66-71
Number of pages	6
DOIs	https://doi.org/10.1109/DSP.2009.4785897
State	Published - 2009
Event	2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009 - Marco Island, FL, United States Duration: Jan 4 2009 → Jan 7 2009

Publication series

Name	2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009, Proceedings

Other

Other	2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009
Country/Territory	United States
City	Marco Island, FL
Period	1/4/09 → 1/7/09

Keywords

Distributed estimation
LMS algorithm
Performance analysis
Wireless sensor networks

Publisher link

10.1109/DSP.2009.4785897

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Mateos, G., Schizas, I. D., & Giannakis, G. B. (2009). Closed-form MSE performance of the distributed LMS algorithm. In 2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009, Proceedings (pp. 66-71). Article 4785897 (2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009, Proceedings). https://doi.org/10.1109/DSP.2009.4785897

Closed-form MSE performance of the distributed LMS algorithm. / Mateos, Gonzalo; Schizas, Ioannis D.; Giannakis, Georgios B.
2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009, Proceedings. 2009. p. 66-71 4785897 (2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009, Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Mateos, G, Schizas, ID & Giannakis, GB 2009, Closed-form MSE performance of the distributed LMS algorithm. in 2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009, Proceedings., 4785897, 2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009, Proceedings, pp. 66-71, 2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009, Marco Island, FL, United States, 1/4/09. https://doi.org/10.1109/DSP.2009.4785897

Mateos G, Schizas ID, Giannakis GB. Closed-form MSE performance of the distributed LMS algorithm. In 2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009, Proceedings. 2009. p. 66-71. 4785897. (2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009, Proceedings). doi: 10.1109/DSP.2009.4785897

Mateos, Gonzalo ; Schizas, Ioannis D. ; Giannakis, Georgios B. / Closed-form MSE performance of the distributed LMS algorithm. 2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009, Proceedings. 2009. pp. 66-71 (2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, DSP/SPE 2009, Proceedings).

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abstract = "Mean-square error (MSE) performance analysis is conducted for a novel distributed least-mean square (D-LMS) algorithm, which is based on consensus, in-network, adaptive estimation using wireless sensor networks (WSNs). For sensor observations that are linearly related to the time-invariant parameter of interest and independent Gaussian data, exact closed-form expressions are derived for the global and sensor-level MSE evolution and steady-state limiting values. Tracking performance is also investigated when the true parameter adheres to a random-walk model. Remarkably, for small step-sizes the results accurately extend to the pragmatic setup whereby sensors acquire temporally-correlated (non-)Gaussian data.",

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AB - Mean-square error (MSE) performance analysis is conducted for a novel distributed least-mean square (D-LMS) algorithm, which is based on consensus, in-network, adaptive estimation using wireless sensor networks (WSNs). For sensor observations that are linearly related to the time-invariant parameter of interest and independent Gaussian data, exact closed-form expressions are derived for the global and sensor-level MSE evolution and steady-state limiting values. Tracking performance is also investigated when the true parameter adheres to a random-walk model. Remarkably, for small step-sizes the results accurately extend to the pragmatic setup whereby sensors acquire temporally-correlated (non-)Gaussian data.

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Closed-form MSE performance of the distributed LMS algorithm

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