Experimental Study on LTE Mobile Network Performance Parameters for Controlled Drone Flights.
LTE
downlink
drone
mobile network
ping
reference signal received power
reference signal received quality
signal to interference and noise ratio
unmanned aerial vehicle
uplink
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
14 Oct 2024
14 Oct 2024
Historique:
received:
23
08
2024
revised:
10
10
2024
accepted:
12
10
2024
medline:
26
10
2024
pubmed:
26
10
2024
entrez:
26
10
2024
Statut:
epublish
Résumé
This paper analyzes the quantitative quality parameters of a mobile communication network in a controlled drone logistic use-case scenario. Based on the analysis of standards and recommendations, the values of key performance indicators (KPIs) are set. As the main network-impacting parameters, reference signal received power (RSRP), reference signal received quality (RSRQ), and signal to interference and noise ratio (SINR) were selected. Uplink (UL), downlink (DL), and ping parameters were chosen as the secondary ones, as they indicate the quality of the link depending on primary parameters. The analysis is based on experimental measurements performed using a Latvian mobile operator's "LMT" JSC infrastructure in a real-life scenario. To evaluate the altitude impact on the selected network parameters, the measurements were performed using a drone as transport for the following altitude values: 40, 60, 90, and 110 m. Network parameter measurements were implemented in automatic mode, allowing switching between LTE4-LTE2 standards, providing the opportunity for more complex analysis. Based on the analysis made, the recommendations for the future mobile networks employed in controlled drone flights should correspond to the following KPI and their values: -100 dBm for RSRP, -16 dB for RSRQ, -5 dB for SINR, 4096 kbps for downlink, 4096 kbps for uplink, and 50 ms for ping. Lastly, recommendations for a network coverage digital twin (DT) model with integrated KPIs are also provided.
Identifiants
pubmed: 39460095
pii: s24206615
doi: 10.3390/s24206615
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : ECSEL Joint Undertaking
ID : 826610
Organisme : European Regional Development Fund
ID : 1.1.1.3/18/A/001 (PVS 3912.6.2)
Organisme : National Research Program
ID : VPP-EM-FOTONIKA2022/1-0001
Organisme : Connecting Europe Facility Digital program
ID : 101133716