Dueling DDQN-Based Adaptive Multi-Objective Handover Optimization for LEO Satellite Networks
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.
| Authors | Po-Heng Chou, Chiapin Wang, Chung-Chi Huang et al. |
|---|---|
| Primary category | cs.IT |
| Published | 4 May 2026 |
| Last updated at source | 9 May 2026 |
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