Analysis of incremental augmented affine projection algorithm for distributed estimation of complex-valued signals

Khalili, A, Rastegarnia, A, Bazzi, WM and Sanei, S ORCID: https://orcid.org/0000-0002-3437-2801, 2017. Analysis of incremental augmented affine projection algorithm for distributed estimation of complex-valued signals. Circuits, Systems, and Signal Processing, 36 (1), pp. 119-136. ISSN 0278-081X

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Abstract

This paper considers the problem of distributed estimation in an incremental network when the measurements taken by the node follow a widely linear model. The proposed algorithm which we refer to it as incremental augmented affine projection algorithm (incAAPA) utilizes the full second order statistical information in the complex domain. Moreover, it exploits spatio-temporal diversity to improve the estimation performance. We derive steady-state performance metric of the incAAPA in terms of the mean-square deviation (MSD). We further derive sufficient conditions to ensure mean-square convergence. Our analysis illustrate that the proposed algorithm is able to process both second order circular (proper) and noncircular (improper) signals. The validity of the theoretical results and the good performance of the proposed algorithm are demonstrated by several computer simulations.

Item Type:	Journal article
Publication Title:	Circuits, Systems, and Signal Processing
Creators:	Khalili, A., Rastegarnia, A., Bazzi, W.M. and Sanei, S.
Publisher:	Springer
Date:	January 2017
Volume:	36
Number:	1
ISSN:	0278-081X
Identifiers:	Number Type 10.1007/s00034-016-0295-6 DOI 295 Publisher Item Identifier
Divisions:	Schools > School of Science and Technology
Record created by:	Linda Sullivan
Date Added:	31 Jan 2018 12:21
Last Modified:	01 Feb 2018 09:02
URI:	https://irep.ntu.ac.uk/id/eprint/32592

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