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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
AlN Combined Overtone Resonators for the 5G mmWave Spectrum
Guofeng Chen, Matteo Rinaldi · 2019-12-10 · via eess.SP updates on arXiv.org

This work presents a new acoustic MEMS resonator technology, dubbed Aluminum Nitride (AlN) Combined Overtone Resonator (COR), capable of addressing the filter requirements for the 5G mmWave spectrum in the 6-40GHz range. The COR exploits the multimodal excitation of two higher-order Lamb waves (2nd and 3rd order Asymmetrical Lamb Waves) in a suspended thin-film AlN plate to transduce a 2-dimensional vibration mode with high electromechanical coupling coefficient kt2 (up to 1.9%) and quality factor Q >1100 at twice the frequency of a fundamental thickness-extensional mode in the same structure. Analytical and finite-element method (FEM) models are developed to describe the working principle of the COR technology and predict the achievable kt2, Q and lithographic frequency tunability. An 8.8 GHz COR prototype was fabricated showing a high kt2~0.3% (using a simple top-electrode-only configuration with a 2-mask process) and a groundbreaking Q~1100 which is the highest ever achieved among piezoelectric resonators above 6 GHz. The f-Q product ~1x10e13 is the highest among all demonstrated piezoelectric resonators with metallic coverage >50%. Additionally, the capability of the COR technology to deliver contiguous filters with bandwidths between 355 and 592 MHz (aggregated BW>2GHz) in the mmWave spectrum, with relaxed lithographic requirements, is demonstrated by FEM.