Analysis of Drone Propagation with Ray Tracing from Sub-6 GHz Upto Terahertz Frequencies in a Real World Urban Environment

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu

3 Sitaatiot (Scopus)
101 Lataukset (Pure)

Abstrakti

Unmanned aerial communication platforms have been recently considered as an effective solution to provide homogeneous and extended network coverage to terrestrial users. Unmanned Aerial Vehicles (UAVs) are expected to increase the network reliability and users' Quality of Experience (QoE). The first target of this paper is to analyze the propagation characteristics of drone transmission at different frequencies i.e., 3.5 GHz, 28 GHz, 60 GHz, and up to 180 GHz with 20GHz step. In the considered setup drone is flying at different heights i.e., from 50m up to 250m altitude and we carry out 3D ray tracing simulations assuming a propagation environment that is defined by the real building data from Helsinki city. Ground users are placed outdoors. We study the validity of a previously proposed geometrical Line of Sight (LOS) probability model between ground user and drone, and based on simulations we propose new modeling parameters. In the second part of the paper, the ray tracing results are compared with the analytical reference model. Finally, a new set of parameters is proposed for tuned analytical model based on acquired ray tracing results. The proposed analytical model provides significantly low Root Mean Square Error (RMSE) when compared with the analytical reference model.

AlkuperäiskieliEnglanti
Otsikko35th International Conference on Information Networking, ICOIN 2021
KustantajaIEEE
Sivut169-174
Sivumäärä6
ISBN (elektroninen)978-1-7281-9100-3
DOI - pysyväislinkit
TilaJulkaistu - 13 tammik. 2021
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaInternational Conference on Information Networking - Jeju Island, Etelä-Korea
Kesto: 13 tammik. 202116 tammik. 2021
Konferenssinumero: 35

Julkaisusarja

NimiThe International conference on information networking
ISSN (elektroninen)1976-7684

Conference

ConferenceInternational Conference on Information Networking
LyhennettäICOIN
Maa/AlueEtelä-Korea
KaupunkiJeju Island
Ajanjakso13/01/202116/01/2021

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