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Partial-Diffusion Least Mean-Square Estimation Over Networks Under Noisy Information Exchange

Authors:
Wael Bazzi
Vahid Vahidpour
Amir Rastegarnia
Azam Khalili

Keywords: adaptive networks; diffusion adaptation; noisy informatin exchange; partial diffusion; sequential, stochastic

Abstract:
Partial diffusion scheme is an effective method for reducing computational load and power consumption in adaptive network implementation. The Information is exchanged among the nodes, usually over noisy links. In this paper, we consider a general version of Partial-Diffusion Least-Mean-Square (PDLMS) algorithm in the presence of various sources of imperfect information exchanges. Like the established PDLMS, we consider two different schemes to select the entries, sequential and stochastic, for transmission at each iteration. Our objective is to analyze the aggregate effect of these perturbations on general PDLMS strategies. Simulation results demonstrate that considering noisy link assumption adds a new complexity to the related optimization problem and the trade-off between communication cost and estimation performance in comparison to ideal case becomes unbalanced. Our simulation results substantiate the effect of noisy links on PDLMS algorithm and verify the theoretical analysis.

Pages: 19 to 25

Copyright: Copyright (c) IARIA, 2019

Publication date: June 30, 2019

Published in: conference

ISSN: 2308-4219

ISBN: 978-1-61208-719-1

Location: Rome, Italy

Dates: from June 30, 2019 to July 4, 2019