Author

Sunisa Kunarak

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Open access Sep 2026

Hybrid Bi-LSTM and Deep Reinforcement Learning for AI-Native Predictive Mobility Management in High-Mobility 5G/6G Networks

Reliable mobility management is critical for high-mobility 5G/6G applications such as smart cities, intelligent transportation systems (ITS), and connected vehicles, where reactive 3GPP handover mechanisms become unreliable as user equipment (UE) velocity increases. This paper proposes a hybrid Bidirectional LSTM (Bi-L...

Normtawan Phuttaamart, Sunisa Kunarak · Machine Learning and Knowled... · 0 citations

Open access Sep 2026

Hybrid DeepMUSIC-Assisted Cooperative Multi-Agent Deep Reinforcement Learning for Intelligent Spectrum Allocation and Interference Management in Multi-UAV 6G Networks

This paper proposes a Hybrid DeepMUSIC-assisted Cooperative Multi-Agent Deep Reinforcement Learning (MADRL) framework for intelligent spectrum allocation and interference management in multi-UAV 6G networks, and achieves the highest network throughput, SINR, spectrum efficiency, and energy efficiency.

Anuchai Bunsan, Sunisa Kunarak · Technologies · 0 citations

A Hybrid Artificial Intelligence Framework for Reliable and Seamless Vertical Handover in Next-Generation Heterogeneous Networks

A Hybrid deep double-Q networks (DDQN)–bidirectional long short-term memory (Bi-LSTM) Framework that integrates bi-directional mobility prediction and DRL-based adaptive decision-making is introduced that highlights the effectiveness of integrating predictive intelligence with reinforcement learning for reliable mobili...

S. Kunarak · 0 citations