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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
Multi-Year Spectral Structure of 6G Candidate Bands at 2....
Amir Hossein Fahim Raouf, Ismail Guvenc · 2026-03-17 · via eess.SP updates on arXiv.org

Mid-band spectrum between 2 and 8 GHz is a critical resource for sixth-generation (6G) systems as it uniquely balances favorable propagation characteristics with scalable bandwidth. Recent U.S. policy highlights candidate bands near 2.7, 4.4, and 7.1 GHz, all of which host substantial federal and non-federal incumbency, including high-power radiolocation and aeronautical telemetry systems. Although these segments are being considered for potential relocation of federal incumbents to enable commercial use, their long-term viability depends on the structural integrity of the spectrum. In such environments, the practical value of spectrum depends on the reliability and contiguity of available spectrum opportunities. This paper presents a measurement-driven feasibility analysis of two representative segments, 2.69-2.9 GHz and 4.4-4.94 GHz, using Software-Defined Radio (SDR) measurements collected during Packapalooza campaigns from 2022 to 2025. Deployment-oriented metrics are introduced to quantify scan-window reliability (SWR), altitude-dependent usable spectrum availability ratio (USAR), largest contiguous clean bandwidth (LCCB), spectral fragmentation, and extreme interference excursions. The results reveal significant year-to-year structural variability. In the 2.69-2.9 GHz band, USAR remains near unity in 2022 and 2023, but drops to approximately 0.65 in 2024 and 0.8 in 2025, accompanied by fragmentation and limited contiguous bandwidth across altitudes. The 4.4-4.94 GHz band exhibits a similar temporal pattern, but with smaller reliability degradation and larger contiguous support, often exceeding several hundred megahertz even during incumbent-dominant periods. The results highlight that wideband feasibility in these candidate bands depends strongly on spectral contiguity and structural stability rather than nominal bandwidth alone.