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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
Effects of CSI Knowledge on Secrecy of Threshold-Selectio...
Chinmoy Kundu, Sarbani Ghose, Telex M. N. Ngatched, Octavia A. D · 2018-03-02 · via eess.SP updates on arXiv.org

This paper considers secrecy of a three node cooperative wireless system in the presence of a passive eavesdropper. The threshold-selection decode-and-forward (DF) relay is considered, which can decode the source message correctly only if a predefined signal-to-noise ratio (SNR) is achieved. The effects of channel state information (CSI) availability on secrecy outage probability (SOP) and ergodic secrecy rate (ESR) are investigated, and closed-form expressions are derived. Diversity is achieved from the direct and relaying paths both at the destination and at the eavesdropper by combinations of maximal-ratio combining (MRC) and selection combining (SC) schemes. An asymptotic analysis is provided when each hop SNR is the same in the balanced case and when it is different in the unbalanced case. The analysis shows that both hops can be a bottleneck for secure communication; however, they do not affect the secrecy identically. While it is observed that CSI knowledge can improve secrecy, the amount of improvement for SOP is more when the required rate is low and for ESR when the operating SNR is also low. It is also shown that the source to eavesdropper link SNR is more crucial for secure communication.