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

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
V
V2EX
WordPress大学
WordPress大学
U
Unit 42
I
InfoQ
A
About on SuperTechFans
宝玉的分享
宝玉的分享
J
Java Code Geeks
博客园 - 司徒正美
爱范儿
爱范儿
Engineering at Meta
Engineering at Meta
G
Google Developers Blog
人人都是产品经理
人人都是产品经理
小众软件
小众软件
Microsoft Security Blog
Microsoft Security Blog
L
LangChain Blog
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
Hugging Face - Blog
Hugging Face - Blog
H
Hackread – Cybersecurity News, Data Breaches, AI and More
aimingoo的专栏
aimingoo的专栏
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
Last Week in AI
Last Week in AI
腾讯CDC
Recent Announcements
Recent Announcements

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
Terahertz-Band Near-Space Communications: From a Physical...
Tianqi Mao, Leyi Zhang, Zhenyu Xiao, Zhu Han, Xiang-Gen Xia · 2022-07-25 · via eess.SP updates on arXiv.org

Facilitated by rapid technological development of the near-space platform stations (NSPS), near-space communication (NS-COM) is envisioned to play a pivotal role in the space-air-ground integrated network for sixth-generation (6G) communications and beyond. In NS-COM, ultra-broadband wireless connectivity between NSPSs and various airborne/spaceborne platforms is required for a plethora of bandwidth-consuming applications, such as NSPS-based Ad hoc networking, in-flight Internet and relaying technology. However, such requirement seems to contradict with the scarcity of spectrum resources at conventional microwave frequencies, which motivates the exploitation of terahertz (THz) band ranging from 0.1 to 10 THz. Due to huge available bandwidth, the THz signals are capable of supporting ultra-high-rate data transmission for NS-COM over 100 Gb/s, which are naturally suitable for the near-space environment with marginal path loss. To this end, this article provides an extensive investigation on the THz-band NS-COM (THz-NS-COM) from a physical-layer perspective. Firstly, we summarize the potential applications of THz communications in the near-space environment, where the corresponding technical barriers are analyzed. Then the channel characteristics of THz-NS-COM and the corresponding modeling strategies are discussed, respectively. Afterwards, three essential research directions are investigated to surpass the technical barriers of THz-NS-COM, i.e., robust beamforming for ultra-massive antenna array, signal processing algorithms against hybrid distortions, and integrated sensing and communications. Several open problems are also provided to unleash the full potential of THz-NS-COM.