Dynamic Adaptation and Multi-Domain Learning for Optimized Interoperability between Heterogeneous Satellite Communication Systems

With the rising demand for seamless global connectivity, heterogeneous satellite systems (i.e. satellite systems operated by different providers) are integrated. This study introduces a new approach to optimizing interoperability between satellite constellations using dynamic adaptation and multi-domain learning. To improve QoS and environment understanding, the framework employs intelligent protocol conversion, real-time network switching, and collaborative learning. The proposed system demonstrates considerable improvement in user satisfaction, QoS metrics, and learning efficiency from the simulation results. The findings underscore the transformational potential of multi-domain learning in the pursuit of satellite network interoperability and scalable, efficient communication systems.

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-04-22
DOI
https://doi.org/10.52783/jisem.v10i38s.6960
Primary Topic
Satellite Communication Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Dynamic Adaptation and Multi-Domain Learning for Optimized Interoperability between Heterogeneous Satellite Communication Systems

Mohammed A. Kadhim
Journal of Information Systems Engineering & Management
Satellite Communication Systems
article

Dynamic Adaptation and Multi-Domain Learning for Optimized Interoperability between Heterogeneous Satellite Communication Systems

Mohammed A. Kadhim
article en

Abstract

With the rising demand for seamless global connectivity, heterogeneous satellite systems (i.e. satellite systems operated by different providers) are integrated. This study introduces a new approach to optimizing interoperability between satellite constellations using dynamic adaptation and multi-domain learning. To improve QoS and environment understanding, the framework employs intelligent protocol conversion, real-time network switching, and collaborative learning. The proposed system demonstrates considerable improvement in user satisfaction, QoS metrics, and learning efficiency from the simulation results. The findings underscore the transformational potential of multi-domain learning in the pursuit of satellite network interoperability and scalable, efficient communication systems.

Journal of Information Systems Engineering & ManagementVol. 10(38s)
Openalex Percentile: Top 88%
Satellite Communication Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.