relation: http://www.eledia.org/students-reports/887/
title: Enhanced Linear Array Clustering via Hilbert Order
creator: BENONI, Arianna
creator: ROCCA, Paolo
creator: ANSELMI, Nicola
creator: MASSA, Andrea
subject: A WC Next Generation Wireless Communications
subject: M AT Analytic Techniques
description: This study investigates the clustering of linear phased arrays (PAs) featuring complex weights. By exploiting the inherent locality-preserving characteristic of the Hilbert curve, an initial reduction of problem dimensionality is performed.  Subsequently, a basic clustering algorithm is employed to enhance the alignment of the radiated pattern with a predetermined reference.  We systematically explore both contiguous and noncontiguous partitions of the Hilbert-ordered list of complex excitations to comprehensively sample the solution space. Representative results, including reference PAs generating steered pencil and shaped beams, are included to highlight the superior performance of the presented approach over conventional k-means algorithms.
publisher: ELEDIA Research Center - University of Trento
date: 2024-05-31
type: Monograph
type: NonPeerReviewed
format: text
language: en
identifier: http://www.eledia.org/students-reports/887/1/Enhanced_Linear_Array_Clustering_via_Hilbert_Order.pdf
identifier:   BENONI, Arianna and ROCCA, Paolo and ANSELMI, Nicola and MASSA, Andrea  (2024) Enhanced Linear Array Clustering via Hilbert Order.  Technical Report. ELEDIA Research Center - University of Trento.