Low-Complexity Multi-Agent Continual Learning for Stacked Intelligent Metasurface-Assisted Secure Communications
Beijing Jiaotong University（北京交通大学）；Nanjing Rongcai Transportation Technology Research Institute Co., Ltd.（南京荣彩交通技术研究院有限公司）；University of New South Wales（新南威尔士大学）；Nanyang Technological University（南洋理工大学）
Enyu Shi, Yiyang Zhu, Jiayi Zhang, Ziheng Liu, Jiakang Zheng, Jiancheng An, Derrick Wing Kwan Ng, Bo Ai, Chau Yuen
备注：
Enyu Shi and Yiyang Zhu contributed equally to this work
Stacked intelligent metasurfaces (SIMs), composed of multiple layers of reconfigurable transmissive metasurfaces, are gaining prominence as a transformative technology for future wireless communication security. This paper investigates the integration of SIM into multi-user multiple-input multiple-output (MIMO) systems to enhance physical layer security. A novel system architecture is proposed, wherein each base station (BS) antenna transmits a dedicated single-user stream, while a multi-layer SIM executes wave-based beamforming in the electromagnetic domain, thereby avoiding the need for complex baseband digital precoding and significantly reducing hardware overhead. To maximize the weighted sum secrecy rate (WSSR), we formulate a joint precoding optimization problem over BS power allocation and SIM phase shifts, which is high-dimensional and non-convex due to the complexity of the objective function and the coupling among optimization variables. To address this, we propose a manifold-enhanced heterogeneous multi-agent continual learning (MHACL) framework that incorporates gradient representation and dual-scale policy optimization to achieve robust performance in dynamic environments with high demands for secure communication. Furthermore, we develop SIM-MHACL (SIMHACL), a low-complexity learning template that embeds phase coordination into a product manifold structure, reducing the exponential search space to linear complexity while maintaining physical feasibility. Simulation results validate that the proposed framework achieves millisecond-level per-iteratio ntraining in SIM-assisted systems, significantly outperforming various baseline schemes, with SIMHACL achieving comparable WSSR to MHACL while reducing computation time by 30\%.
A Survey on Stacked Intelligent Metasurfaces: Fundamentals, Recent Advances, and Challenges
University of Luxembourg（卢森堡大学）；National Institute of Technology Warangal（瓦朗加尔国立技术学院）；National and Kapodistrian University of Athens（雅典国家与卡波迪斯特里阿斯大学）；University of Illinois Chicago（伊利诺伊大学芝加哥分校）
Reconfigurable intelligent surface has recently emerged as a promising technology for shaping the wireless environment by leveraging massive low-cost reconfigurable elements. Prior works mainly focus on a single-layer metasurface that lacks the capability of suppressing multiuser interference. By contrast, we propose a stacked intelligent metasurface (SIM)-enabled transceiver design for multiuser multiple-input single-output downlink communications. Specifically, the SIM is endowed with a multilayer structure and is deployed at the base station to perform transmit beamforming directly in the e…
Two-Layer Stacked Intelligent Metasurfaces: Balancing Performance and Complexity
Nanyang Technological University（南洋理工大学）；CNRS and CentraleSupélec, Institute of Electronics and Digital Technologies（法国国家科学研究中心与中央理工-高等电力学院，电子与数字技术研究所）；King’s College London, Department of Engineering - Centre for Telecommunications Research（伦敦国王学院，工程学院-电信研究中心）；Research Institute for Digital Future, Khalifa University（哈利法大学数字未来研究所）；Princeton University（普林斯顿大学）
Stacked Intelligent Metasurface-Aided Wave-Domain Signal Processing: From Communications to Sensing and Computing
Nanyang Technological University（南洋理工大学）；Research Institute for Digital Future, Khalifa University（哈利法大学数字未来研究所）；CentraleSupelec, University Paris-Saclay（中央理工-苏佩莱克学院，巴黎萨克雷大学）；University of Southampton（南安普顿大学）
Are Stacked Intelligent Metasurfaces (SIMs) Better than Single-layer Reconfigurable Intelligent Surfaces (RISs) for Wideband Multi-user MIMO Communication Systems?
Department of Informatics and Telecommunications（信息与电信系）；National and Kapodistrian University of Athens（国家与kapodistrian大学）；National Inter-University Consortium for Telecommunications (CNIT)（电信联合大学 consortium）；Sapienza University of Rome（罗马萨皮恩扎大学）
Efficient Alternating Optimization for Hybrid Digital-Wave Beamforming in SIM-Assisted Cell-Free Massive MIMO
Hanyang University（汉阳大学）；Northeastern University London（伦敦东北大学）；King’s College London（伦敦国王学院）；CNRS and CentraleSupélec, Institute of Electronics and Digital Technologies (IETR)（法国国家科学研究中心与中央理工-苏裴蕾斯，电子与数字技术研究所）
Distributed Electromagnetic Neural Networks for Task-Oriented Semantic Communications
University of Electronic Science and Technology of China（电子科技大学）；The University of British Columbia（不列颠哥伦比亚大学）；University of Oulu（奥卢大学）；Khalifa University（哈利法大学）
