UAV Mobility Tracing in 72 Urban Environments

This data is collected using Panda5gSim, which is available on GitHub: https://github.com/yemenlinux/panda5gsim

It contains 3D transformations and ray-tracing Line-of-Sight (LoS) conditions between two Unmanned Aerial Vehicles (UAVs) and ten ground mobile users.

The data is collected by generating 72 synthetic urban environments based on ITU-R P.1410 urban configuration.

Number of runs: 3 for each scenario.

Scenario number 1: files started with "no_buildings*"

Scenario number 2: files started with "with_buildings*"

Number of environments in each file: 72.

Each urban environment is simulated for 120 seconds.

Fields:

Column Name : Description

Time : Time stamp

RxNode : Receiver’s (mobile ground user) name.

TxNode : Transmitter’s or UAV's (airborne access point) name.

RayLoS : Ray-tracing LoS for the omnidirectional antenna.

dRayLoS : Ray-tracing LoS for the 3GPP directional antenna.

nBuildings : Number of buildings between UAV and ground user.

v_rx : Velocity of mobile ground user.

v_tx : Velocity of UAV (airborne access point).

phi : The azimuth (heading) angle between the transmitter and the receiver.

theta : The elevation (pitch) angle between the transmitter and the receiver.

d3D : The direct distance in 3D space between the transmitter and the receiver.

d2D : The horizontal projection of the distance between the transmitter and the receiver.

Gain : The antenna gain for the 3GPP directional antenna is calculated by the relative transformations of the receiver as seen from the transmitter.

Transforms : The transformation tuple. The transformation tuple contains the following: (1) the receiver’s transformation; (2) the transmitter’s transformation; (3) the relative transformation of the receiver as seen from the transmitter; (4) the receiver’s identification; (5) the transmitter’s identification.

h : The height difference between the receiver and the transmitter.

Environment : The environment name is formatted as (Urban\_$\alpha$\_$\beta$\_$\gamma$).

本数据集通过Panda5gSim采集，该工具可在GitHub获取：https://github.com/yemenlinux/panda5gsim

它包含两架无人机（Unmanned Aerial Vehicle, UAV）与十名地面移动用户之间的三维变换及射线追踪视距（Line-of-Sight, LoS）条件。

本数据集通过基于ITU-R P.1410城市配置生成72个合成城市环境采集而得。

运行次数：每个场景3次。

场景1：以"no_buildings*"开头的文件

场景2：以"with_buildings*"开头的文件

每个文件中的环境数量：72

每个城市环境的模拟时长为120秒。

字段：

列名：描述

Time：时间戳

RxNode：接收方（地面移动用户）名称

TxNode：发送方或无人机（空中接入点）名称

RayLoS：全向天线的射线追踪视距

dRayLoS：3GPP定向天线的射线追踪视距

nBuildings：无人机与地面用户之间的建筑物数量

v_rx：地面移动用户的速度

v_tx：无人机（空中接入点）的速度

phi：发送方与接收方之间的方位角（航向角）

theta：发送方与接收方之间的仰角（俯仰角）

d3D：发送方与接收方之间的三维空间直接距离

d2D：发送方与接收方之间距离的水平投影

Gain：3GPP定向天线的增益，由接收方相对于发送方的变换计算得出

Transforms：变换元组，包含以下内容：（1）接收方的变换；（2）发送方的变换；（3）接收方相对于发送方的变换；（4）接收方标识；（5）发送方标识

h：接收方与发送方之间的高度差

Environment：环境名称格式为（Urban_$alpha$_$eta$_$gamma$）