Modeling Air-to-Ground Path loss下载

weixin_39820535 2019-10-02 06:30:19

The reliable prediction of coverage footprint result-
ing from an airborne wireless radio base station, is at utmost
importance, when it comes to the new emerging applications
of air-to-ground wireless services. These applications include the
rapid recovery of damaged terrestrial wireless infrastruc
相关下载链接：//download.csdn.net/download/weixin_42383695/10457965?utm_source=bbsseo

...全文

20 回复打赏收藏转发到动态举报

写回复

回复

切换为时间正序

请发表友善的回复…

发表回复

The reliable prediction of coverage footprint result- ing from an airborne wireless radio base station, is at utmost importance, when it comes to the new emerging applications of air-to-ground wireless services. These applications include the rapid recovery of damaged terrestrial wireless infrastructure due to a natural disaster, as well as the fulfillment of sudden wireless traffic overload in certain spots due to massive movement of crowds. In this paper, we propose a statistical propagation model for predicting the air-to-ground path loss between a low altitude platform and a terrestrial terminal. The prediction is based on the urban environment properties, and is dependent on the elevation angle between the terminal and the platform. The model shows that air-to-ground path loss is following two main propagation groups, characterized by two different path loss profiles. In this paper we illustrate the methodology of which the model was deduced, as well as we present the different path loss profiles including the occurrence probability of each.

Topics Active Perception in Robotics Adaptive Robotic Systems Aerial Robotics Aerial Robotics: Control Aerial Robotics: Design and Mechanism Aerial Robotics: Detection Aerial Robotics: Learning and Adaptive Systems Aerial Robotics: Mechanics and Control A

Lecture theme: AI-for-Science: The next wave of artificial intelligenceSession 1:Overview：AI-for-Science: The next wave of artificialAI BoomingAI: From Mimicking Human to Discovering the WorldScience: Discover and Change the WorldFour Paradigms of ScienceClosing the Loop of Scientific DiscoverySession 2:Solving Scientific EquationsGraphormer for Molecular ModelingMolecular SimulationAI Models for Molecular SimulationGraphormerGraphormer: ResultsMD Simulation for SARS-COV-2The “Wedge” Effect of NTDDeepVortexNet for Fluid ModelingMeteorological SimulationPhysics-informed Neural NetworkFrom Derivative-based to Monte-CarloDeep Vortex NetworkSession 3:Mining Experimental ObservationsLorentzNet for Particle DetectionParticle DetectionJet Analysis and Group EquivarianceProblems with Existing AI ModelsLorentzNetExperimental ResultsSPT-Scientific Language ModelSPT: Foundation Model for ScienceEffective Training: A System WorkEffective Inference: Double PromptsExperimental ResultsSession 4:Discovering New ScienceAI for New Physics DetectionForce Field DecomposingLearning Non-conservative DynamicsExperimental ResultsTarget ApplicationsMore of Our Recent ResearchMicrosoft Research AI4Science

CVPR论文列表，中英对照

CVPR 2021最全论文开放，附所有pdf下载链接！

下载资源悬赏专区

12,887

社区成员

12,439,232

社区内容

发帖

与我相关

我的任务

其他技术论坛（原bbs）

社区管理员

加入社区

近7日
近30日
至今

加载中

查看更多榜单

社区公告

暂无公告

试试用AI创作助手写篇文章吧

+ 用AI写文章