Title :
Closed-Form MSE Performance of the Distributed LMS Algorithm
Author :
Mateos, Gonzalo ; Schizas, Ioannis D. ; Giannakis, Georgios B.
Author_Institution :
Dept. of ECE, Univ. of Minnesota, Minneapolis, MN
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.
Keywords :
Gaussian processes; least mean squares methods; wireless sensor networks; adaptive estimation; distributed LMS algorithm; distributed least-mean square algorithm; independent Gaussian data; mean-square error performance analysis; random-walk model; wireless sensor networks; Adaptive estimation; Analysis of variance; Closed-form solution; Covariance matrix; Fluctuations; Least squares approximation; Performance analysis; Signal processing algorithms; Steady-state; Wireless sensor networks; LMS algorithm; Wireless sensor networks; distributed estimation; performance analysis;
Conference_Titel :
Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, 2009. DSP/SPE 2009. IEEE 13th
Conference_Location :
Marco Island, FL
Print_ISBN :
978-1-4244-3677-4
Electronic_ISBN :
978-1-4244-3677-4
DOI :
10.1109/DSP.2009.4785897
