DOI: 10.5061/dryad.zw3r228k9
title: Accelerating development in UAV network digital twins with a flexible simulation framework

description: Unmanned aerial vehicles (UAVs) enhance coverage and provide flexible
 deployment in 5G and next-generation wireless networks. The performance of
 such wireless networks can be improved by developing new navigation and
 wireless adaptation approaches in digital twins (DTs). However, challenges
 such as complex propagation conditions and hardware complexities in
 real-world scenarios introduce a realism gap with the DTs. Moreover, while
 using real-time full-stack protocols in DTs enables subsequent deployment
 and testing in a real-world environment, development in DTs requires high
 computational complexity and involves a long development time. In this
 paper, we develop a measurement-calibrated Matlab-based simulation
 framework to accelerate the development cycle to replicate performance in
 a full-stack UAV wireless network DT. In particular, we use the
 DT from the NSF AERPAW platform and compare its reports with those
 generated by our developed simulation framework in wireless networks with
 similar settings. In both environments, we observe comparable results in
 terms of RSRP measurement, hence motivating iterative use of the developed
 simulation environment with the DT.
description: # UAV Trajectory, RSRP, and Throughput Datasets (AERPAW Lake Wheeler) ---
 We have submitted our emulated and simulated UAV trajectory measurement
 data, post-processing scripts (MATLAB and Python), and high-quality static
 figures in PDF format. These data support wireless link analysis and UAV
 mobility modeling. In this dataset, "trajectory" refers to the
 latitude, longitude, and altitude of the UAV recorded over time. --- ##
 List of Included Files *
 `fixed_autonomous_trajectory_dataset_and_post_processing.zip`\ A
 compressed archive containing all datasets for: * fixed trajectory
 (emulation and simulation approaches) * autonomous trajectory
 (simulation)\ The archive includes CSV files for all four base stations,
 figures in PDF format, and all associated MATLAB and Python
 post-processing scripts.\ See detailed file and variable descriptions in
 the sections below. --- ## File Descriptions ###
 **fixed_trajectory_rsrp_emulation** **Included files:** *
 `LW1_fixed_trajectory.csv` * `LW2_fixed_trajectory.csv` *
 `LW3_fixed_trajectory.csv` * `LW4_fixed_trajectory.csv` *
 `plot_rsrp_emulation.pdf` * `plot_rsrp_distance_emulation.pdf` * MATLAB
 post-processing scripts Each CSV contains raw UAV measurement data from
 the NSF AERPAW digital twin platform for one of four LTE base stations
 along a fixed trajectory. PDF files provide high-quality figures showing
 RSRP over time and versus distance. **CSV variables:** * *time*: Timestamp
 of measurement (YYYY-MM-DD HH:MM:SS.ssssss) * *Altitude*: UAV altitude
 above ground (meters, m) * *BatteryVolts*: UAV battery voltage (volts, V)
 * *GPSFix*: Number of valid GPS fixes (count) * *Latitude*: UAV latitude
 (decimal degrees) * *Longitude*: UAV longitude (decimal degrees) *
 *NumberOfSatellites*: Number of GPS satellites (count) * *Pitch*: UAV
 pitch angle (radians) * *Roll*: UAV roll angle (radians) * *VelocityX*:
 UAV velocity, X-axis (meters/second, m/s) * *VelocityY*: UAV velocity,
 Y-axis (meters/second, m/s) * *VelocityZ*: UAV velocity, Z-axis
 (meters/second, m/s) * *Yaw*: UAV yaw angle (radians) * *blerDl*: Downlink
 block error rate (fraction 0–1) * *blerUl*: Uplink block error rate
 (fraction 0–1) * *brateDl*: Downlink bitrate (kilobits/second, kbps) *
 *brateUl*: Uplink bitrate (kilobits/second, kbps) * *buff*: Buffer size
 (internal, diagnostic) * *cc*: Component carrier index * *cfo*: Carrier
 frequency offset (kilohertz, kHz) * *mcsDl*: Downlink modulation and
 coding scheme index * *mcsUl*: Uplink modulation and coding scheme index *
 *num*: Frame number (diagnostic) * *pci*: Physical Cell ID of serving base
 station * *pl*: Path loss (decibels, dB) * *rsrp*: Reference Signal
 Received Power (dBm) * *snr*: Signal-to-Noise Ratio (dB) * *ta_us*: Timing
 advance (microseconds, µs) * *turbo*: Turbo decoder iterations
 (diagnostic) --- ### **fixed_trajectory_rsrp_simulation** **Included
 files:** * `LW1_log.csv` * `LW2_log.csv` * `LW3_log.csv` * `LW4_log.csv` *
 `plot_rsrp_simulation.pdf` * `plot_rsrp_distance_simulation.pdf` * MATLAB
 post-processing scripts Each CSV contains simulated measurement data for a
 fixed UAV trajectory at one base station. PDF files are static plots of
 simulation results. **CSV variables:** * *time*: Timestamp (YYYY-MM-DD
 HH:MM:SS.sss) * *Longitude*: UAV longitude (decimal degrees) * *Latitude*:
 UAV latitude (decimal degrees) * *Altitude*: UAV altitude (meters, m) *
 *rsrp*: Reference Signal Received Power (dBm) * *snr*: Signal-to-Noise
 Ratio (dB) * *datarate*: Downlink data rate (megabits/second, Mbps) ---
 ### **autonomous_trajectory_rsrp_simulation** **Included files:** *
 `LW1_log.csv` * `LW2_log.csv` * `LW3_log.csv` * `LW4_log.csv` *
 `plot_rsrp_simulation.pdf` * `plot_throughput_distance_vs_time_lw12.pdf` *
 `plot_throughput_distance_vs_time_lw34.pdf` * MATLAB and Python
 post-processing scripts Each CSV contains simulated measurement data for
 an autonomous (algorithm-driven) UAV trajectory at one base station. PDF
 files provide static plots for time-varying RSRP and throughput. **CSV
 variables:** * *time*: Timestamp (YYYY-MM-DD HH:MM:SS.sss) * *longitude*:
 UAV longitude (decimal degrees) * *latitude*: UAV latitude (decimal
 degrees) * *altitude*: UAV altitude (meters, m) * *speed*: UAV speed
 (meters/second, m/s); may be blank in some rows * *rsrp*: Reference Signal
 Received Power (dBm) * *snr*: Signal-to-Noise Ratio (dB) * *datarate*:
 Downlink data rate (megabits/second, Mbps) * *Prx*: Received power at
 receiver (dBm) --- ## Recommended Software * **CSV files:** Open with
 [LibreOffice Calc](https://www.libreoffice.org/), Microsoft Excel, or
 Google Sheets. * **PDF files:** View with Adobe Acrobat Reader. *
 **Scripts:** View with Notepad, TextEdit, VS Code, or any text editor.  *
 **ZIP file:** Unzip with built-in OS utilities, 7-Zip, or WinRAR. --- ##
 Further Information For methodology, simulation framework, or support,
 see:\
 [https://github.com/mhossenece/UAVFlexSimFramework](https://github.com/mhossenece/UAVFlexSimFramework)\ For questions, contact the corresponding author. ---