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[2602.13238] Securing SIM-Assisted Wireless Networks via Quantum Reinforcement Learning
Summary
This paper presents a novel hybrid quantum reinforcement learning framework, Q-PPO, designed to enhance the security of SIM-assisted wireless networks by optimizing transmit power and phase shifts.
Why It Matters
As wireless networks become increasingly vulnerable to eavesdropping, this research introduces a cutting-edge approach using quantum reinforcement learning to improve security measures. The findings could significantly impact the design of secure communication systems, making them more efficient and robust against threats.
Key Takeaways
- Q-PPO framework outperforms traditional DRL methods in securing wireless networks.
- Achieves approximately 15% higher secrecy rates and 30% faster convergence.
- Utilizes a hybrid classical-quantum policy architecture for better optimization.
Computer Science > Networking and Internet Architecture arXiv:2602.13238 (cs) [Submitted on 29 Jan 2026] Title:Securing SIM-Assisted Wireless Networks via Quantum Reinforcement Learning Authors:Le-Hung Hoang, Quang-Trung Luu, Dinh Thai Hoang, Diep N. Nguyen, Van-Dinh Nguyen View a PDF of the paper titled Securing SIM-Assisted Wireless Networks via Quantum Reinforcement Learning, by Le-Hung Hoang and 4 other authors View PDF HTML (experimental) Abstract:Stacked intelligent metasurfaces (SIMs) have recently emerged as a powerful wave-domain technology that enables multi-stage manipulation of electromagnetic signals through multilayer programmable architectures. While SIMs offer unprecedented degrees of freedom for enhancing physical-layer security, their extremely large number of meta-atoms leads to a high-dimensional and strongly coupled optimization space, making conventional design approaches inefficient and difficult to scale. Moreover, existing deep reinforcement learning (DRL) techniques suffer from slow convergence and performance degradation in dynamic wireless environments with imperfect knowledge of passive eavesdroppers. To overcome these challenges, we propose a hybrid quantum proximal policy optimization (Q-PPO) framework for SIM-assisted secure communications, which jointly optimizes transmit power allocation and SIM phase shifts to maximize the average secrecy rate under power and quality-of-service constraints. Specifically, a parameterized quantum circuit is...
