Deep Learning Based Antenna Design and Beam-Steering Capabilities for Millimeter-Wave Applications

Deep Learning Based Antenna Design and Beam-Steering Capabilities for Millimeter-Wave Applications

In this study, a deep neural network (DNN) is implemented to soft computation of the dual-band circularly polarized bone-shaped patch antenna (BSPA) at 28 GHz and 38 GHz for 5G applications. Via a simulated database of 150 BSPAs, a DNN model is constructed on a 5-layer system using an adaptive learn...

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Bibliographic Details
Main Authors: Ahmed M. Montaser, Korany R. Mahmoud
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Deep learning
artificial neural network
optimization algorithm
mm-wave antennas
circular polarization
beamforming technique
Online Access:https://ieeexplore.ieee.org/document/9585682/

Internet

https://ieeexplore.ieee.org/document/9585682/

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