A review of multibeam phased array antennas as LEO satellite constellation ground station

G He, X Gao, L Sun, R Zhang - IEEE Access, 2021 - ieeexplore.ieee.org
Small satellites in low Earth orbit (LEO) are typically organized as a satellite constellation.
The satellite number of a LEO satellite constellation would be several hundred or even tens …

Artificial intelligence for adaptive and reconfigurable antenna arrays: A review

F Zardi, P Nayeri, P Rocca… - IEEE Antennas and …, 2020 - ieeexplore.ieee.org
This article provides an overview of a few applications of artificial intelligence (AI) in
adaptive and reconfigurable antenna arrays. In particular, AI proves to be more robust than …

Fully automated design method based on reinforcement learning and surrogate modeling for antenna array decoupling

Z Wei, Z Zhou, P Wang, J Ren, Y Yin… - … on Antennas and …, 2022 - ieeexplore.ieee.org
Modern electromagnetic (EM) device design generally relies on extensive iterative
optimizations by designers using simulation software (eg, CST), which is a very time …

Machine learning‐enabled two‐port wideband MIMO hybrid rectangular dielectric resonator antenna for n261 5G NR millimeter wave

JK Rai, P Ranjan, S Kumar… - International Journal …, 2024 - Wiley Online Library
In this article, a two‐port multiple‐input multiple‐output (MIMO) hybrid rectangular dielectric
resonator antenna (DRA) with machine learning (ML) approach for the n261 5G New Radio …

Neural network applications in smart antenna arrays: A review

A Rawat, RN Yadav, SC Shrivastava - AEU-International Journal of …, 2012 - Elsevier
Techniques employed in the synthesis of antenna arrays vary from complex analytical
methods to iterative numerical methods based on optimisation algorithms. The drawback of …

Application of machine learning in electromagnetics: Mini-review

MSI Sagar, H Ouassal, AI Omi, A Wisniewska… - Electronics, 2021 - mdpi.com
As an integral part of the electromagnetic system, antennas are becoming more advanced
and versatile than ever before, thus making it necessary to adopt new techniques to …

Consensus deep neural networks for antenna design and optimization

ZŽ Stanković, DI Olćan, NS Dončov… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
We present a general approach for antenna design and optimization based on consensus of
results from a number of independently trained deep neural networks (DNNs). The aim of …

Planar array diagnosis by means of an advanced Bayesian compressive processing

M Salucci, A Gelmini, G Oliveri… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
The detection of faulty radiators in planar antenna arrays is addressed in a probabilistic
framework and it is solved through an innovative multitask Bayesian compressive sensing …

Machine learning in electromagnetics: A review and some perspectives for future research

D Erricolo, PY Chen, A Rozhkova… - 2019 International …, 2019 - ieeexplore.ieee.org
We review machine learning and its applications in a wide range of electromagnetic
problems, including radar, communication, imaging and sensing. We extensively discuss …

Optimizing the gain and directivity of a microstrip antenna with metamaterial structures by using artificial neural network approach

M Sağık, O Altıntaş, E Ünal, E Özdemir… - Wireless Personal …, 2021 - Springer
The purpose of this study is to improve the gain and directivity of the microstrip patch
antenna by means of metamaterial (MTM) structures. As it is known, antennas have power …