Machine learning-based technique for directivity prediction of a compact and highly efficient 4-port MIMO antenna for 5G millimeter wave applications

Machine learning-based technique for directivity prediction of a compact and highly efficient 4-port MIMO antenna for 5G millimeter wave applications

Miniaturized Millimeter Wave (mm-wave) MIMO antenna arrays with an observed 10-dB impedance broad bandwidth of 3.7 GHz (25.785–29.485) are the focus of this study's design and analysis for a 5G application. Rogers RT/duroid 5880, a low-loss dielectric material, is utilized in the antenna's...

Full description

Saved in:
Bibliographic Details
Main Authors: Md Ashraful Haque, Kamal Hossain Nahin, Jamal Hossain Nirob, Md Kawsar Ahmed, Narinderjit Singh Sawaran Singh, Liton Chandra Paul, Abeer D. Algarni, Mohammed ElAffendi, Abdelhamied A. Ateya
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Results in Engineering
Subjects:
28 GHz
5G technology
Mm-wave
MIMO antenna
Machine learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2590123024013616
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items