Supervised Learning Based Real-Time Adaptive Beamforming On-board Multibeam Satellites

Satellite communications (SatCom) are crucial for global connectivity, especially in the era of emerging technologies like 6G and narrowing the digital divide. Traditional SatCom systems struggle with efficient resource management due to static multibeam configurations, hindering quality of service...

Full description

Saved in:
Bibliographic Details
Published in:arXiv.org 2023-11
Main Authors: Ortiz, Flor, Vasquez-Peralvo, Juan A, Querol, Jorge, Lagunas, Eva, Gonzalez Rios, Jorge L, Marcele O K Mendonca, Garces, Luis, Victor Monzon Baeza, Chatzinotas, Symeon
Format: Article
Language:English
Subjects:
Algorithms
Beamforming
Circular polarization
Effective isotropic radiated power (EIRP)
Geosynchronous orbits
Machine learning
New technology
Payloads
Real time
Resource management
Satellite communications
Sidelobes
Supervised learning
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Satellite communications (SatCom) are crucial for global connectivity, especially in the era of emerging technologies like 6G and narrowing the digital divide. Traditional SatCom systems struggle with efficient resource management due to static multibeam configurations, hindering quality of service (QoS) amidst dynamic traffic demands. This paper introduces an innovative solution - real-time adaptive beamforming on multibeam satellites with software-defined payloads in geostationary orbit (GEO). Utilizing a Direct Radiating Array (DRA) with circular polarization in the 17.7 - 20.2 GHz band, the paper outlines DRA design and a supervised learning-based algorithm for on-board beamforming. This adaptive approach not only meets precise beam projection needs but also dynamically adjusts beamwidth, minimizes sidelobe levels (SLL), and optimizes effective isotropic radiated power (EIRP).
ISSN:2331-8422