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eess.SP updates on arXiv.org

ECG-biometrics-bench: A Unified Framework for Reproducible Benchmarking of ECG Biometrics Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning Towards Improving Speaker Distance Estimation through Generative Impulse Response Augmentation Federated Learning with Hypergradient-based Online Update of Aggregation Weights Soft Graph Diffusion Transformer for MIMO Detection SPLICE: Latent Diffusion over JEPA Embeddings for Conformal Time-Series Inpainting Sequential Inference for Gaussian Processes: A Signal Processing Perspective Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Framework Recent Advances in mm-Wave and Sub-THz/THz Oscillators for FutureG Technologies Cross-Subject Generalization for EEG Decoding: A Survey of Deep Learning Methods Super-resolution Multi-signal Direction-of-Arrival Estimation by Hankel-structured Sensing and Decomposition Hankel and Toeplitz Rank-1 Decomposition of Arbitrary Matrices with Applications to Signal Direction-of-Arrival Estimation Adaptive Transform Coding for Semantic Compression EdgeSpike: Spiking Neural Networks for Low-Power Autonomous Sensing in Edge IoT Architectures Sparse Graph Learning from Sparse Data via Fiedler Number Maximization A Deep Learning Model for Battery State Prediction towards Intelligent Energy Management Transfer Learning for Tonal Noise Prediction in VRF Units Using Thermodynamic and Vibration Signals EVT-Based Generative AI for Tail-Aware Channel Estimation Monitoring exposure-length variations in submarine power cables using distributed fiber-optic sensing BandRouteNet: An Adaptive Band Routing Neural Network for EEG Artifact Removal Phase-Separated Complex Hilbert PCA on Markerless 3D Pose Estimation Data: A Global Phase Network and Its Extension to a Continuous Field on the Body Surface Selective Correlation Based Knowledge Distillation for Ground Reaction Force Estimation Deep Learning-Enabled Dissolved Oxygen Sensing in Biofouling Environments for Ocean Monitoring Speech Enhancement Based on Drifting Models Robust and Clinically Reliable EEG Biomarkers: A Cross Population Framework for Generalizable Parkinson's Disease Detection An AI-Based Supervisory Measurement Integrity Validation Layer for Cyber-Resilient AC/DC Protection in Inverter-Based Microgrids Explainable AI in Speaker Recognition -- Making Latent Representations Understandable Time-Localized Parametric Decomposition of Respiratory Airflow for Sub-Breath Analysis NAKUL-Med: Spectral-Graph State Space Models with Dynamics Kernels for Medical Signals An Algorithm for On-Sensor Agnostic Detection of Changes in Human Activity for Ultra-Low-Power Applications
A Survey on Stacked Intelligent Metasurfaces: Fundamental...
Chandan Kumar Sheemar, Wali Ullah Khan, Sourabh Solanki, George · 2026-03-06 · via eess.SP updates on arXiv.org

Reconfigurable intelligent surfaces (RISs) enable programmable control of wireless propagation. Beyond environmental deployments, integrating metasurfaces at the antenna front end allows direct manipulation of the radiated electromagnetic field and enables wave-domain signal processing. In this context, stacked intelligent metasurfaces (SIMs) have recently been proposed as an advanced architecture in which multiple programmable metasurface layers interact through wave propagation, enabling richer and more flexible electromagnetic transformations than conventional single-layer designs. By leveraging cascaded wave-matter interactions at the transmitter or receiver front end, SIMs substantially expand the design space of programmable wireless systems. This survey provides a comprehensive overview of SIMs technologies from the electromagnetic processing perspective, covering their physical principles, modeling frameworks, hardware realizations, and emerging architectural designs. We review existing modeling approaches based on cascaded operators, multiport impedance formulations, and network parameter representations, and discuss their implications for scalable optimization and system design. The survey further examines key communication functionalities enabled by front-end metasurface processing, including communication performance optimization, near-field and wideband transmission, learning-driven control, integrated sensing and communications, and emerging architectures such as cell-free and non-terrestrial networks. Finally, we identify open research problems related to physical modeling, scalability, hardware-algorithm co-design, and network integration, and outline promising directions toward realizing SIM-based antenna front ends as fully programmable electromagnetic processors for future sixth-generation (6G) wireless systems.