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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
Indoor Propagation Measurements with Sekisui Transparent ...
Chethan K. Anjinappa, Ashwini P. Ganesh, Ozgur Ozdemir, Kris Rid · 2022-03-16 · via eess.SP updates on arXiv.org

One of the critical challenges of operating with the terahertz or millimeter-wave wireless networks is the necessity of at least a strong non-line-of-sight (NLoS) reflected path to form a stable link. Recent studies have shown that an economical way of enhancing/improving these NLoS links is by using passive metallic reflectors that provide strong reflections. However, despite its inherent radio advantage, metals can dramatically influence the landscape's appearance - especially the indoor environment. A conceptual view of escaping this is by using transparent reflectors. In this work, for the very first time, we evaluate the wireless propagation characteristics of passive transparent reflectors in an indoor environment at 28 GHz, 39 GHz, 120 GHz, and 144 GHz bands. In particular, we investigate the penetration loss and the reflection characteristics at different frequencies and compare them against the other common indoor materials such as ceiling tile, clear glass, drywall, plywood, and metal. The measurement results suggest that the transparent reflector, apart from an obvious advantage of transparency, has a higher penetration loss than the common indoor materials (excluding metal) and performs similarly to metal in terms of reflection. Our experimental results directly translate to better reflection performance and preserving the radio waves within the environment than common indoor materials, with potential applications in controlled wireless communication.