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 …
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
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 …
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
Modern electromagnetic (EM) device design generally relies on extensive iterative
optimizations by designers using simulation software (eg, CST), which is a very time …
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
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 …
resonator antenna (DRA) with machine learning (ML) approach for the n261 5G New Radio …
Neural network applications in smart antenna arrays: A review
Techniques employed in the synthesis of antenna arrays vary from complex analytical
methods to iterative numerical methods based on optimisation algorithms. The drawback of …
methods to iterative numerical methods based on optimisation algorithms. The drawback of …
Application of machine learning in electromagnetics: Mini-review
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 …
and versatile than ever before, thus making it necessary to adopt new techniques to …
Consensus deep neural networks for antenna design and optimization
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 …
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
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 …
framework and it is solved through an innovative multitask Bayesian compressive sensing …
Machine learning in electromagnetics: A review and some perspectives for future research
We review machine learning and its applications in a wide range of electromagnetic
problems, including radar, communication, imaging and sensing. We extensively discuss …
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
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 …
antenna by means of metamaterial (MTM) structures. As it is known, antennas have power …