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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
Multi-Functional Programmable Metasurfaces for 6G and Beyond
Xu Gan, Xidong Mu, Yuanwei Liu, Marco Di Renzo, Josep Miquel Jor · 2025-12-07 · via eess.SP updates on arXiv.org

The sixth-generation and beyond (B6G) networks are envisioned to support advanced applications that demand high-speed communication, high-precision sensing, and high-performance computing. To underpin this multi-functional evolution, energy- and cost-efficient programmable metasurfaces (PMs) have emerged as a promising technology for dynamically manipulating electromagnetic waves. This paper provides a comprehensive survey of representative multi-functional PM paradigms, with a specific focus on achieving \emph{full-space communication coverage}, \emph{ubiquitous sensing}, as well as \emph{intelligent signal processing and computing}. i) For simultaneously transmitting and reflecting surfaces (STARS)-enabled full-space communications, we elaborate on their operational protocols and pivotal applications in supporting efficient communications, physical layer security, unmanned aerial vehicle networks, and wireless power transfer. ii) For PM-underpinned ubiquitous sensing, we formulate the signal models for the PM-assisted architecture and systematically characterize its advantages in near-field and cooperative sensing, while transitioning to the PM-enabled transceiver architecture and demonstrating its superior performance in multi-band operations. iii) For advanced signal processing and computing, we explore the novel paradigm of stacked intelligent metasurfaces (SIMs), investigating their implementation in wave-domain analog processing and over-the-air mathematical computing. Finally, we identify key research challenges and envision future directions for multi-functional PMs towards B6G.