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Enhancing Gain Through Optimal Antenna Element Distribution in a Thinned Array Configuration

Authors :
Michael Ortiz
Md Nazim Uddin
Marisol Roman Guerra
Elias A. Alwan
Source :
IEEE Open Journal of Antennas and Propagation, Vol 4, Pp 1176-1186 (2023)
Publication Year :
2023
Publisher :
IEEE, 2023.

Abstract

This paper presents an array thinning approach for a 25-element antenna array arranged in a $5\times5$ grid at 5.4 GHz. Our goal is to eliminate a maximum number of antenna elements with minor gain loss and hence reduce the array size, weight, cost, and power requirements. Consequently, the space saved by the thinned array configuration presents opportunities to integrate additional antennas and hardware, allowing for a low-profile antenna-in-package. Our study showed that a 64% array reduction (from 25 to 9 probe-fed patch antennas) achieved an array gain comparable to a full array configuration. As such, various 9-element configurations for testing were generated through the thinning process and optimized using the genetic algorithm. These configurations were then validated using full-wave simulations. Results show that all configurations that preserved the effective area while maintaining symmetry along all axes showed a minimal effect on gain reduction. Specifically, the best thinning configuration resulted in a loss of only 1.82 dB in simulation at broadside compared to a fully populated $5\times5$ array. The exact configuration also showed beam scanning performance from −45° to +45° (viz. 90°). A prototype was fabricated and tested for each of the thinned configurations. The measured gain of the optimal 9-element thinned array configuration showed excellent agreement with the simulations.

Details

Language :
English
ISSN :
26376431
Volume :
4
Database :
Directory of Open Access Journals
Journal :
IEEE Open Journal of Antennas and Propagation
Publication Type :
Academic Journal
Accession number :
edsdoj.0bf7635c0d194f7c82e741d2af07e02e
Document Type :
article
Full Text :
https://doi.org/10.1109/OJAP.2023.3331322