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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
Optimizing the 4G--5G Migration: A Simulation-Driven Road...
Desire Guel, Justin Pegd-Windé Kouraogo, Kouka Kouakou Nakoulma · 2025-12-30 · via eess.SP updates on arXiv.org

Deploying fifth-generation (5G) networks in emerging markets demands a balance between performance targets and constraints in budget, spectrum, and infrastructure. We use MATLAB simulations to quantify how radio and architectural levers - MIMO (beamforming, diversity, spatial multiplexing), carrier aggregation (CA), targeted spectrum refarming to New Radio (NR), mmWave propagation with blockage/rain, and Non-Standalone (NSA) versus Standalone (SA) cores - affect capacity, coverage, latency, and interference robustness, with D2D and M2M as complements to wide-area access. Beamforming improves cell-edge SNR by about 3-6 dB, while spatial multiplexing dominates at moderate/high SNR via multi-stream gains. Throughput scales strongly with CA: increasing from 1 to 5x20-MHz carriers raises peak rate from about 200 Mb/s to about 1 Gb/s at 30 dB SNR; water-filling adds 5-12% over equal power at mid-SNR. Targeted mid-band refarming to NR increases median throughput by 60-90% in urban and 40-70% in rural scenarios when sub-1-GHz layers preserve coverage. At 28 GHz, rain and human blockage add about 8-30 dB excess loss, so viable mmWave deployment concentrates in LOS hot zones with narrow-beam arrays and short inter-site distances. NSA delivers broader initial coverage than SA by reusing LTE/EPC, while SA becomes attractive as transport improves (e.g., >= 10 Gb/s and < 5 ms RTT) and site density grows. We synthesize these results into a practical roadmap: start NR on NSA, prioritize CA-centric spectrum strategies with focused refarming, densify selectively in demand hotspots, and migrate to SA as backhaul and device ecosystems mature.