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

WordPress大学
WordPress大学
大猫的无限游戏
大猫的无限游戏
B
Blog
阮一峰的网络日志
阮一峰的网络日志
IT之家
IT之家
Hugging Face - Blog
Hugging Face - Blog
博客园 - 【当耐特】
Jina AI
Jina AI
博客园 - 聂微东
T
The Blog of Author Tim Ferriss
宝玉的分享
宝玉的分享
L
LangChain Blog
M
MIT News - Artificial intelligence
Blog — PlanetScale
Blog — PlanetScale
腾讯CDC
酷 壳 – CoolShell
酷 壳 – CoolShell
Y
Y Combinator Blog
F
Fortinet All Blogs
H
Help Net Security
B
Blog RSS Feed
J
Java Code Geeks
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
Apple Machine Learning Research
Apple Machine Learning Research
S
SegmentFault 最新的问题

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
Impact of Array Configuration on Head-Mounted Display Per...
Alexander Marinšek, Xuesong Cai, Lieven De Strycker, Fredrik Tuf · 2023-12-12 · via eess.SP updates on arXiv.org

Immersing a user in life-like extended reality (XR) scenery using a head-mounted display (HMD) with a constrained form factor and hardware complexity requires remote rendering on a nearby edge server or computer. Millimeter-wave (mmWave) communication technology can provide sufficient data rate for wireless XR content transmission. However, mmWave channels exhibit severe sparsity in the angular domain. This means that distributed antenna arrays are required to cover a larger angular area and to combat outage during HMD rotation. At the same time, one would prefer fewer antenna elements/arrays for a lower complexity system. Therefore, it is important to evaluate the trade-off between the number of antenna arrays and the achievable performance to find a proper practical solution. This work presents indoor 28 GHz mmWave channel measurement data, collected during HMD mobility, and studies the dominant eigenmode (DE) gain. DE gain is a significant factor in understanding system performance since mmWave channel sparsity and eigenmode imbalance often results in provisioning the majority of the available power to the DE. Moreover, it provides the upper performance bounds for widely-adopted analog beamformers. We propose 3 performance metrics - gain trade-off, gain volatility, and minimum service trade-off - for evaluating the performance of a multi-array HMD and apply the metrics to indoor 28 GHz channel measurement data. Evaluation results indicate, that 3 arrays provide stable temporal channel gain. Adding a 4th array further increases channel capacity, while any additional arrays do not significantly increase physical layer performance.