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arXiv · 2605.02416

Dueling DDQN-Based Adaptive Multi-Objective Handover Optimization for LEO Satellite Networks

Po-Heng Chou·Chiapin Wang·Chung-Chi Huang·Kuan-Hao Chen
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Abstract

In this paper, we propose a dueling double deep Q-network (DDQN)-based adaptive multi-objective handover framework for low Earth orbit (LEO) satellite networks. The proposed method enables dynamic trade-off learning among throughput, blocking probability, and switching cost under time-varying network conditions. Simulation results demonstrate that the proposed approach consistently outperforms conventional baselines, achieving up to 10.3% throughput improvement and near-zero blocking under typical operating conditions.

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Po-Heng Chou, Chiapin Wang, Chung-Chi Huang, Kuan-Hao Chen. 2026-05-04. Dueling DDQN-Based Adaptive Multi-Objective Handover Optimization for LEO Satellite Networks. https://arxiv.org/abs/2605.02416

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