惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

罗磊的独立博客
Y
Y Combinator Blog
Recent Announcements
Recent Announcements
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
V
Visual Studio Blog
MyScale Blog
MyScale Blog
M
MIT News - Artificial intelligence
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
T
The Blog of Author Tim Ferriss
Martin Fowler
Martin Fowler
博客园 - 【当耐特】
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
宝玉的分享
宝玉的分享
Engineering at Meta
Engineering at Meta
WordPress大学
WordPress大学
Google DeepMind News
Google DeepMind News
C
Check Point Blog
Last Week in AI
Last Week in AI
F
Fortinet All Blogs
博客园 - 聂微东
Blog — PlanetScale
Blog — PlanetScale
H
Help Net Security
GbyAI
GbyAI
云风的 BLOG
云风的 BLOG

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
Toward Agile and Cooperative LEO Satellite Beam-Hopping N...
Xinyi Huang, Bodong Shang, Meixia Tao · 2026-05-30 · via eess.SP updates on arXiv.org

Low-Earth orbit (LEO) satellite beam-hopping (BH) technology is emerging as a promising approach to meet the ever-increasing global connectivity demands, enabling agile, on-demand coverage. LEO satellite BH can address the spatio-temporal non-uniformity of ground user traffic by dynamically allocating capacity and optimizing network performance. Cooperative multi-satellite BH enables joint transmission and interference avoidance to improve received signal quality. This article provides a comprehensive paradigm of BH, detailing its key dimensions, strategies, and architectures. Through exploration of key challenges, including beam pattern design, on-demand scheduling, and interference management, this paper identifies the potential applications of BH, ranging from adaptive capacity allocation for hotspot areas, low-power Internet-of-Things (IoT), delay-sensitive services, to massive connectivity support. Furthermore, a system-level analysis is presented, including key metrics, models of inter-beam and inter-satellite interference, and cooperative joint transmission, and a case study is provided to demonstrate the performance benefits of BH with cooperative transmission. Several promising future research directions are discussed to guide the future development of LEO satellite BH networks.