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International Journal of Antennas and Propagation
Volume 2017 (2017), Article ID 9845050, 8 pages
https://doi.org/10.1155/2017/9845050
Research Article

Application of a Sparsity Pattern and Region Clustering for Near Field Sparse Approximate Inverse Preconditioners in Method of Moments Simulations

1Computer Science Department, University of Alcalá, Madrid, Spain
2NewFasant S.L., Guadalajara, Spain

Correspondence should be addressed to Carlos Delgado; se.hau@odagled.solrac

Received 18 May 2017; Revised 28 September 2017; Accepted 8 October 2017; Published 31 October 2017

Academic Editor: Nicolas Pinel

Copyright © 2017 Carlos Delgado et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This document presents a technique for the generation of Sparse Inverse Preconditioners based on the near field coupling matrices of Method of Moments simulations where the geometry has been partitioned in terms of regions. A distance parameter is used to determine the sparsity pattern of the preconditioner. The rows of the preconditioner are computed in groups at a time, according to the number of unknowns contained in each region of the geometry. Two filtering thresholds allow considering only the coupling terms with a significant weight for a faster generation of the preconditioner and storing only the most significant preconditioner coefficients in order to decrease the memory required. The generation of the preconditioner involves the computation of as many independent linear least square problems as the number of regions in which the geometry is partitioned, resulting in very good scalability properties regarding its parallelization.