Artificial intelligence for satellite communication: A review
Satellite communication offers the prospect of service continuity over uncovered and under-
covered areas, service ubiquity, and service scalability. However, several challenges must …
covered areas, service ubiquity, and service scalability. However, several challenges must …
A review on the design and optimization of antennas using machine learning algorithms and techniques
This paper presents a focused and comprehensive literature survey on the use of machine
learning (ML) in antenna design and optimization. An overview of the conventional …
learning (ML) in antenna design and optimization. An overview of the conventional …
A generative machine learning-based approach for inverse design of multilayer metasurfaces
The synthesis of a metasurface exhibiting a specific set of desired scattering properties is a
time-consuming and resource-demanding process, which conventionally relies on many …
time-consuming and resource-demanding process, which conventionally relies on many …
Prior-knowledge-guided deep-learning-enabled synthesis for broadband and large phase shift range metacells in metalens antenna
A prior-knowledge-guided deep-learning-enabled (PK-DL) synthesis method is proposed for
enhancing the transmission bandwidth and phase shift range of metacells used for the …
enhancing the transmission bandwidth and phase shift range of metacells used for the …
Machine learning in antenna design: An overview on machine learning concept and algorithms
With the growth and wide variety of available data, advanced processing, and affordable
data storage, machine learning is witnessing great attention in finding optimized solutions in …
data storage, machine learning is witnessing great attention in finding optimized solutions in …
Support vector regression to accelerate design and crosspolar optimization of shaped-beam reflectarray antennas for space applications
DR Prado, JA Lopez-Fernandez… - … on Antennas and …, 2018 - ieeexplore.ieee.org
A machine learning technique is applied to the design and optimization of reflectarray
antennas to considerably accelerate computing time without compromising accuracy. In …
antennas to considerably accelerate computing time without compromising accuracy. In …
Full-range amplitude–phase metacells for sidelobe suppression of metalens antenna using prior-knowledge-guided deep-learning-enabled synthesis
A prior-knowledge-guided deep-learning-enabled (PK-DL) synthesis method is proposed to
design the metacells with the full-range amplitude and phase control for suppressing the …
design the metacells with the full-range amplitude and phase control for suppressing the …
Towards efficient reflectarray digital twins-an EM-driven machine learning perspective
The concept of digital twins (DTs) for reflectarray (RA) unit cells (UCs) is discussed and
implemented by exploiting electromagnetic-driven machine learning (ML) techniques …
implemented by exploiting electromagnetic-driven machine learning (ML) techniques …
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 …
Phased antenna array beamforming using convolutional neural networks
In this research, a novel method of phased antenna array beamforming using a
convolutional neural network is presented. Given a desired 2-dimensional radiation pattern …
convolutional neural network is presented. Given a desired 2-dimensional radiation pattern …