DOI: 10.5061/dryad.r7sqv9sr3
title: AERPAW: Aerial Android-based 4G measurements of public AT&T cell towers from a tethered Helikite

description: A tethered Helikite (a combination of a Helium balloon and a kite),
 carrying a commercial off-the-shelf (COTS) Android phone, was flown within
 the North Campus of NC State University, Raleigh, NC, during the 2023
 Packapalooza festival. 4G cellular KPIs of public AT&T base
 stations were logged by the phone, using a custom Android App. These KPIs
 were synchronized with the Helikite position information: latitude,
 longitude, and altitude above ground. This dataset is shared in .csv
 format, along with .kml files of the 4G KPIs, for visualization on Google
 Earth. Analysis of this dataset can reveal insights into the variation in
 physical-layer KPIs with the aerial user's position, along with the
 ability of commercial public base stations to serve aerial users in urban
 regions.
description: # AERPAW: Aerial Android-based 4G measurements of public AT&T cell
 towers from a tethered Helikite Dataset DOI:
 [10.5061/dryad.r7sqv9sr3](10.5061/dryad.r7sqv9sr3) ## Description of the
 data and file structure This dataset
 (Aerpaw_PawPrints_Packapalooza_Helikite.zip) contains cellular LTE
 measurements from an Android phone carried by a tethered HeliKite, over a
 duration of approximately one and a half hours, within the North Campus of
 NC State University. The Helikite eventually rose to an altitude of 120
 meters. RSRP, RSRQ, and RSSI values of public AT&T networks are
 shared, along with their physical cell ID. A GPS logger onboard the
 HeliKite recorded the latitude, longitude, and altitude. Radio and GPS
 measurements were recorded at one-second intervals and merged based on the
 timestamp. **Dataset Content:** The dataset is shared in the form of a zip
 file, named aerpaw_pawprints_packapalooaza_helikit.zip, containing the
 following folders: * Logs: Contains the *pawprints_4G.csv* raw log file
 with the KPIs * KMLs: Contains representative KML files, indicating
 variation in RSRP and RSRQ with location  * Results: Contains .png images
 of the representative KMLs and some Matlab plots of variation in KPIs with
 time and altitude. **KPI Logs**:\ The *Logs* folder within the dataset
 contains timestamped 4G cellular KPIs in *"pawprints_4G.csv"*.
 KPIs were logged at intervals of 1 second. KPIs of differtent AT&T
 cell towers, identified by their PCI, are logged in separate rows. A
 column, named "*is_connected*", indicates whether the UAV was
 connected to the corresponding PCI at each row. Users of the dataset can
 filter using this row to analyze KPIs only for the connected cell or
 filter using the "*pci*" column to analyze a specific cell. Each
 row contains the following KPIs: * Timestamp of the measurement row: *
 Column name = *timestamp*. Units = milliseconds. * Unix timestamp of the
 measurement in milliseconds elapsed since the Unix epoch (Jan 1, 1970). *
 Relative time since start of measurement: * Column name =
 *rel_time*. Units = seconds. - Helikite longitude: * Column name =
 *longitude.* Units = degrees.  - Helikite latitude * Column name =
 *latitude.* Units = degrees.  - Helikite altitude above ground: * Column
 name = *altitude*. Units = meters.  - Physical cell identity (PCI):  *
 Column name = *pci*. No units. * Indicates the physical layer cell
 identity of the cell. - Cell Identity (CI):  * Column name = *ci*. No
 units. * Unique global identifier for a cell sector.  -
 "Connected" flag: * Column name = *is_connected*. Units = 1 or
 0. * An integer flag, which indicates if the UAV was connected to the
 corresponding PCI at the corresponding timestamp. 1 indicates connected. 0
 indicates not connected. Users can filter on this field to only choose log
 rows corresponding to the connected PCI, e.g., to analyze the distribution
 of the connected RSRP. - Tracking area code (TAC): * Column name = *tac*.
 No units - EARFCN (E-UTRA Absolute Radio Frequency Channel Number): *
 Column name = *earfcn*. No units * Received Signal Reference Power
 (RSRP):  * Column name = *rsrp*. Units = dBm. * Received Signal Strength
 Indicator (RSSI):  * Column name = *rssi*. Units = dBm.  * Reference
 Signal Received Quality (RSRQ): * Column name = *rsrq*. Units = dB.  *
 Arbitrary Strength Unit (ASU): * Column name = *asu.* No units. * An
 integer mapping of signal strength from 0 to 97, as specified in 3GPP TS
 27.007. Higher values indicate better signal strength. The value of 0 maps
 to RSRP below -140 dBm and the value of 97 maps to RSRP above -44 dBm. ASU
 = RSRP + 140  * Timing advance (TA):  * Column name = *ta*. No units. * An
 instruction sent from base stations to cellular users, providing them with
 a specific timing offset, to ensure that the uplink signals arrive in time
 at the base station. Adjusted in relation to the distance of the user from
 the base station. **KMLs:** KML files for RSRP, and RSRQ are included for
 the connected cell, named *packapalooza_rsrp.kml* and
 *packapalooza_rsrq.kml* respectively. It is also possible to generate KMLs
 of KPIs per cell tower. *Representative Results:* PNG files showing the
 variation in RSRP, RSRQ, and LTE signal quality (as determined by RSRP and
 RSRQ thresholds) with UAV location are included in the *./Results* folder.
 Details are as follows: *helikite_rsrp_rssi_vs_time.png:* Variation in
 HeliKite RSRP and RSSI with time and altitude *helikite_rsrq
 \_vs_time.png:* Variation in HeliKite RSRQ and RSSI with time and altitude
 *helikite_rssi.png*: Variation in HeliKite RSSI with its position, as
 visualized on Google Earth using a KML file.
 *helikite_rsrq.png*: Variation in HeliKite RSRQ with its position, as
 visualized on Google Earth using a KML file.
 *helikite_rsrp.png:* Variation in HeliKite RSRP with its position, as
 visualized on Google Earth using a KML file.
 *helikite_quality.png:* Variation in HeliKite's received signal
 quality (calculated using LTE thresholds on RSRP and RSRQ) with its
 position, as visualized on Google Earth using a KML file. ###
 Code/software The KMLs can be opened with Google Earth.  The .csv log
 files can be analyzed using MATLAB or the Python *pandas* library.