LEO Satellite Handover Using Advantage Actor-Critic Algorithm in Giant Constellation Network

Low Earth Orbit (LEO) satellite network is a crucial component of the Space-Air-Ground Integrated Network (SAGIN) architecture and Non-Terrestrial Networks (NTN). It can provide global, real-time, and seamless broadband data services to many users, playing a critical role in emergencies such as disaster relief. This paper proposes an Advantage Actor-Critic (A2C) algorithm-based handover strategy for LEO satellite networks to address high handover frequency, data transmission blockage, and optimal access selection issues. The strategy considers five handover factors: available satellite bandwidth, elevation angle, signal reception strength, potential service time, and service quality. At first, the handover problem is modelled as a combinatorial optimization problem, subsequently transformed into a Markovian Action-Value Function (MAVF) based Multi-Agent Markov Decision Process (MAMDP), and solved in the framework of the A2C algorithm. The results of simulations illustrate the superior performance of the proposed handover strategy compared to five handover strategies, namely RH, MFC, MST, MADQL, and MIS, in terms of both convergence and practicality. The proposed strategy reduces the number of average handovers by up to 58% and improves signal stability, with enhancements reaching up to 39%. Additionally, this strategy significantly lowers the probability of data transmission blockage and the number of handover failures (handover failure rate), effectively ensuring user communication quality.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Aerospace and Electronic Systems
Published
2025-05-14
DOI
https://doi.org/10.1109/taes.2025.3570255
Citations
2
Primary Topic
Satellite Communication Systems
Type
article
Field-Weighted Citation Impact
9.99
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

LEO Satellite Handover Using Advantage Actor-Critic Algorithm in Giant Constellation Network

Shaohua Wan, Qingqi Pei, Cong Li, Chen Chen et al.
2 citations
IEEE Transactions on Aerospace and Electronic Systems
Satellite Communication Systems
9.99
article

LEO Satellite Handover Using Advantage Actor-Critic Algorithm in Giant Constellation Network

Shaohua Wan, Qingqi Pei, Cong Li, Chen Chen, Tong Mu, Chao Tong
article en
2 citations

Abstract

Low Earth Orbit (LEO) satellite network is a crucial component of the Space-Air-Ground Integrated Network (SAGIN) architecture and Non-Terrestrial Networks (NTN). It can provide global, real-time, and seamless broadband data services to many users, playing a critical role in emergencies such as disaster relief. This paper proposes an Advantage Actor-Critic (A2C) algorithm-based handover strategy for LEO satellite networks to address high handover frequency, data transmission blockage, and optimal access selection issues. The strategy considers five handover factors: available satellite bandwidth, elevation angle, signal reception strength, potential service time, and service quality. At first, the handover problem is modelled as a combinatorial optimization problem, subsequently transformed into a Markovian Action-Value Function (MAVF) based Multi-Agent Markov Decision Process (MAMDP), and solved in the framework of the A2C algorithm. The results of simulations illustrate the superior performance of the proposed handover strategy compared to five handover strategies, namely RH, MFC, MST, MADQL, and MIS, in terms of both convergence and practicality. The proposed strategy reduces the number of average handovers by up to 58% and improves signal stability, with enhancements reaching up to 39%. Additionally, this strategy significantly lowers the probability of data transmission blockage and the number of handover failures (handover failure rate), effectively ensuring user communication quality.

IEEE Transactions on Aerospace and Electronic SystemsVol. 61(5)
Xidian University (CN), China Academy of Space Technology (CN)
Openalex Percentile: Top 3%
Satellite Communication Systems
9.99
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.