Capacity-Aware Multi-UE Handover Optimization for LEO Satellite Networks Using Dueling DDQN
Abstract
Frequent handovers and finite satellite capacity make multi-user mobility management challenging in low Earth orbit (LEO) satellite networks. This paper develops a capacity-aware multi-user handover framework based on a double deep Q-network (DDQN) with a dueling architecture. Both training and evaluation employ sequential user equipment (UE) processing with shared satellite occupancy, while action masking excludes invisible or capacity-infeasible satellites. The state incorporates satellite visibility, achievable link quality, remaining capacity, previous association, short-term visibility, and time information. A fixed multi-criteria reward balances throughput, blocking, handover cost, connection persistence, and short-term visibility, while expert trajectories are used only for replay-buffer initialization. Simulations under different UE densities and satellite capacities show that the proposed framework maintains high average throughput per UE and low blocking rates with moderate handover frequency. Ablation results show that removing the remaining-capacity vector has only a limited effect on performance when sequential occupancy tracking and feasible-action masking are retained.
Related
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BibTeX
@misc{chou2026capacityaware,
title = {{Capacity-Aware Multi-UE Handover Optimization for LEO Satellite Networks Using Dueling DDQN}},
author = {Po-Heng Chou and Chiapin Wang and Chung-Chi Huang and Kuan-Hao Chen and Chien-Yu Chen},
howpublished = {arXiv},
year = {2026},
month = nov,
doi = {10.48550/arxiv.2605.02416},
eprint = {2605.02416},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2605.02416},
}
RIS
TY - UNPB
TI - Capacity-Aware Multi-UE Handover Optimization for LEO Satellite Networks Using Dueling DDQN
AU - Po-Heng Chou
AU - Chiapin Wang
AU - Chung-Chi Huang
AU - Kuan-Hao Chen
AU - Chien-Yu Chen
PY - 2026
DA - 2026/11/01
PB - arXiv
DO - 10.48550/arxiv.2605.02416
UR - https://arxiv.org/abs/2605.02416
AB - Frequent handovers and finite satellite capacity make multi-user mobility management challenging in low Earth orbit (LEO) satellite networks. This paper develops a capacity-aware multi-user handover framework based on a double deep Q-network (DDQN) with a dueling architecture. Both training and evaluation employ sequential user equipment (UE) processing with shared satellite occupancy, while action masking excludes invisible or capacity-infeasible satellites. The state incorporates satellite visibility, achievable link quality, remaining capacity, previous association, short-term visibility, and time information. A fixed multi-criteria reward balances throughput, blocking, handover cost, connection persistence, and short-term visibility, while expert trajectories are used only for replay-buffer initialization. Simulations under different UE densities and satellite capacities show that the proposed framework maintains high average throughput per UE and low blocking rates with moderate handover frequency. Ablation results show that removing the remaining-capacity vector has only a limited effect on performance when sequential occupancy tracking and feasible-action masking are retained.
ER -