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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
Analog-Digital Beam Focusing for Line of Sight Wide-Apert...
Jiyoung Yun, Hojun Rho, Wan Choi · 2024-04-07 · via eess.SP updates on arXiv.org

Enhancing high-speed wireless communication in the future relies significantly on harnessing high frequency bands effectively. These bands predominantly operate in line-of-sight (LoS) paths, necessitating well-configured antenna arrays and beamforming techniques for optimal spectrum utilization. Maximizing the potential of LoS multiple-input multiple-output (MIMO) systems, which are crucial for achieving high spectral efficiency, heavily depends on this. As the costs and power demands of mixed-signal devices in high frequency bands make a fully-digital architecture impractical for large-scale MIMO setups, our focus shifts to a hybrid analog-digital hardware configuration. Yet, analog processors' limitations restrict flexibility within arrays, necessitating a nuanced understanding of hardware constraints for optimal antenna configuration design. We explore array design that optimizes the spectral efficiency of hybrid systems, considering hardware constraints. We propose an optimal antenna configuration, leveraging the prolate matrix structure of the LoS channel between two planar arrays. Building on the optimal array configuration, we introduce a low-complexity explicit analog-digital beam focusing scheme that exploits the asymptotic behavior of the LoS channel matrix in the near-field region. Simulation results validate that the proposed antenna configuration and beam focusing scheme achieves near-optimal performance across a range of signal-to-noise ratios with low computational complexity, even under arbitrary rotations relative to the communication link.