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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 Integrated Sensing and Communication with Int...
Ahmed Magbool, Vaibhav Kumar, Qingqing Wu, Marco Di Renzo, Mark · 2024-01-28 · via eess.SP updates on arXiv.org

The emergence of technologies demanding high data rates and precise sensing, such as autonomous vehicles and IoT devices, has driven the popularity of integrated sensing and communication (ISAC) in recent years. ISAC provides a framework for communication and sensing, where both functionalities are performed simultaneously or in a coordinated manner. There are two levels of integration in ISAC: radio-communications coexistence (RCC), where communication and radar systems use distinct hardware, waveforms, and signal processing but share the spectrum; and dual-function radar-communications (DFRC), where communication and sensing share the same hardware, waveform, and signal processing. At the architectural level, intelligent metasurfaces are a key enabler for the sixth-generation (6G) of wireless communication due to their ability to control the propagation environment efficiently. With the potential to enhance communication and sensing performance, numerous studies have explored the gains of metasurfaces for ISAC. Moreover, certain ISAC frameworks address limitations associated with reconfigurable intelligent surfaces (RIS) for communication. Thus, integrating ISAC with metasurfaces enhances both technologies. This survey reviews the literature on metasurface-assisted ISAC, detailing challenges and opportunities. To provide a comprehensive overview, we begin with fundamentals of ISAC and metasurfaces. The paper summarizes state-of-the-art studies on metasurface-assisted ISAC, focusing on metasurfaces as separate entities between the transmitter and receiver (known as RIS) and emphasizing RCC and DFRC. We also review work on holographic ISAC, where metasurfaces are part of the transmitter and receiver. For each category, lessons learned, challenges, opportunities, and research directions are highlighted.