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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
Lightwave Power Transfer-Enabled Underwater Optical ISAC ...
Kapila W. S. Palitharathna, Constantinos Psomas, Ioannis Krikidi · 2025-11-05 · via eess.SP updates on arXiv.org

In this paper, we propose a lightwave power transfer-enabled underwater optical integrated sensing and communication (O-ISAC) system, where an access point (AP) mounted on a seasurface ship transmits lightwave signals to two nodes, namely ($i$) a seabed sensor that harvests energy and transmits uplink information to the AP, and ($ii$) a sensing target whose position is estimated by the AP using an array of pinhole cameras. To capture practical deployment conditions, the ship attitude variation is modeled through its roll, pitch, and yaw angles, each following a Gaussian distribution under low-to-moderate sea states. Closed-form approximations are derived for the mean squared error (MSE) of target localization and the achievable uplink data rate. Analytical and simulation results demonstrate excellent agreement, validating the proposed models and derived expressions, while revealing the fundamental communication-sensing tradeoff in the O-ISAC system. The results further provide valuable design insights, including the optimal camera placement on the ship to minimize localization error, achieving a minimum MSE of $10^{-2}$ $\text{m}^2$ with multiple cameras under roll, pitch, and yaw angle variation of $10^{\circ}$, and the optimal harvest-use ratio of $0.55$ for the considered setup.