Modeling and Performance Evaluation of Distributed Satellite Antennas: Space Is Much Closer Than One Might Think
Abstract
Distributed satellites can deliver broadband connectivity directly to commercial handsets. In the formation of arrays (FoA) architecture, cooperating satellites synthesize a large aperture whoseextent depends on their number, arrangement, and spacing, with intersatellite distances ranging from tens of meters to hundreds of kilometers. For representative S-band geostationary and low-Earth-orbit configurations, the Fraunhofer distance may exceed the nadir link range at spacings on the order of a hundred meters. Therefore, accurate assessment of FoA performance across satellite populations and spacings requires spherical-wave modeling for users in the radiative near field, below the formation's Fraunhofer distance. Planar models of satellite positions, array orientations, and user locations must also be assessed against spherical geometries accounting for orbital and Earth curvature. This paper combines these models to quantify how simplifying assumptions affect throughput and outage probability. Numerical results show that multi-antenna precoding based on a local plane-wave approximation within each satellite array closely matches the spherical-wave reference. A global plane-wave approximation can instead cause severe losses, including full outage. In the investigated scenarios, formation curvature has little impact, whereas neglecting Earth curvature overestimates low-Earth-orbit throughput. These findings clarify when geometric and propagation approximations remain reliable and demonstrate that, for large distributed antenna apertures, space is much closer than one might think.
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BibTeX
@misc{bacci2026modeling,
title = {{Modeling and Performance Evaluation of Distributed Satellite Antennas: Space Is Much Closer Than One Might Think}},
author = {Giacomo Bacci and Riccardo De Gaudenzi and Marco Luise and Luca Sanguinetti},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.10876},
eprint = {2610.10876},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.10876},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Modeling and Performance Evaluation of Distributed Satellite Antennas: Space Is Much Closer Than One Might Think
AU - Giacomo Bacci
AU - Riccardo De Gaudenzi
AU - Marco Luise
AU - Luca Sanguinetti
PY - 2026
DA - 2026/10/07
PB - arXiv
DO - 10.48550/arxiv.2610.10876
UR - https://arxiv.org/abs/2610.10876
AB - Distributed satellites can deliver broadband connectivity directly to commercial handsets. In the formation of arrays (FoA) architecture, cooperating satellites synthesize a large aperture whoseextent depends on their number, arrangement, and spacing, with intersatellite distances ranging from tens of meters to hundreds of kilometers. For representative S-band geostationary and low-Earth-orbit configurations, the Fraunhofer distance may exceed the nadir link range at spacings on the order of a hundred meters. Therefore, accurate assessment of FoA performance across satellite populations and spacings requires spherical-wave modeling for users in the radiative near field, below the formation's Fraunhofer distance. Planar models of satellite positions, array orientations, and user locations must also be assessed against spherical geometries accounting for orbital and Earth curvature. This paper combines these models to quantify how simplifying assumptions affect throughput and outage probability. Numerical results show that multi-antenna precoding based on a local plane-wave approximation within each satellite array closely matches the spherical-wave reference. A global plane-wave approximation can instead cause severe losses, including full outage. In the investigated scenarios, formation curvature has little impact, whereas neglecting Earth curvature overestimates low-Earth-orbit throughput. These findings clarify when geometric and propagation approximations remain reliable and demonstrate that, for large distributed antenna apertures, space is much closer than one might think.
ER -