Documenti full-text disponibili:
|
Documento PDF (English)
- Richiede un lettore di PDF come Xpdf o Adobe Acrobat Reader
Disponibile con Licenza: Salvo eventuali più ampie autorizzazioni dell'autore, la tesi può essere liberamente consultata e può essere effettuato il salvataggio e la stampa di una copia per fini strettamente personali di studio, di ricerca e di insegnamento, con espresso divieto di qualunque utilizzo direttamente o indirettamente commerciale. Ogni altro diritto sul materiale è riservato.
Download (8MB)
|
Abstract
Unmanned Aerial Vehicles (UAV), also known as "drones", are attracting increasing attention as enablers for many technical applications and services, and this trend is likely to continue in the near future. UAVs are expected to be used extensively in civil and military applications where aerial surveillance and assistance in emergency situations are key factors. UAVs can be more useful and flexible in reaction to specific events, like natural disasters and terrorist attacks since they are faster to deploy, easier to reconfigure and assumed to have better communication means due to their improved position in the sky, improved visibility over ground, and reduced hindrance for propagation. In this regard, UAV enabled communications emerge as one of the most promising solutions for setting-up the next-generation mobile networks, with a special focus on the extension of coverage and capacity of mobile radio networks for 5G applications and beyond. However, air-to-ground (A2G) propagation conditions are likely to be different and more challenging than those experienced by traditional piloted aircraft. For this reason, knowledge of this specific propagation channel – together with the UAV antenna design and placement - is paramount for defining an efficient communication system and for evaluating its performance.
This PhD thesis tackles this challenge, and it aims at further investigating the narrowband properties of the air-to-ground propagation channel by means of GPU accelerated ray launching simulations for 5G communications and beyond.
As a conclusion, this PhD thesis might bring deep insights into the air-to-ground channel characteristics and UAV antenna design, which can be helpful for designing UAV communication networks and evaluating or optimising their performances in a fast and reliable manner, with no need for exhausting – multiple - in-field measurement campaigns.
Abstract
Unmanned Aerial Vehicles (UAV), also known as "drones", are attracting increasing attention as enablers for many technical applications and services, and this trend is likely to continue in the near future. UAVs are expected to be used extensively in civil and military applications where aerial surveillance and assistance in emergency situations are key factors. UAVs can be more useful and flexible in reaction to specific events, like natural disasters and terrorist attacks since they are faster to deploy, easier to reconfigure and assumed to have better communication means due to their improved position in the sky, improved visibility over ground, and reduced hindrance for propagation. In this regard, UAV enabled communications emerge as one of the most promising solutions for setting-up the next-generation mobile networks, with a special focus on the extension of coverage and capacity of mobile radio networks for 5G applications and beyond. However, air-to-ground (A2G) propagation conditions are likely to be different and more challenging than those experienced by traditional piloted aircraft. For this reason, knowledge of this specific propagation channel – together with the UAV antenna design and placement - is paramount for defining an efficient communication system and for evaluating its performance.
This PhD thesis tackles this challenge, and it aims at further investigating the narrowband properties of the air-to-ground propagation channel by means of GPU accelerated ray launching simulations for 5G communications and beyond.
As a conclusion, this PhD thesis might bring deep insights into the air-to-ground channel characteristics and UAV antenna design, which can be helpful for designing UAV communication networks and evaluating or optimising their performances in a fast and reliable manner, with no need for exhausting – multiple - in-field measurement campaigns.
Tipologia del documento
Tesi di dottorato
Autore
Arpaio, Maximilian James
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
33
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Ray Launching, Unmanned Aerial Vehicle (UAV), GPU, Antennas, Narrowband Channel, Propagation, 5G networks.
URN:NBN
DOI
10.6092/unibo/amsdottorato/9849
Data di discussione
15 Giugno 2021
URI
Altri metadati
Tipologia del documento
Tesi di dottorato
Autore
Arpaio, Maximilian James
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
33
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Ray Launching, Unmanned Aerial Vehicle (UAV), GPU, Antennas, Narrowband Channel, Propagation, 5G networks.
URN:NBN
DOI
10.6092/unibo/amsdottorato/9849
Data di discussione
15 Giugno 2021
URI
Statistica sui download
Gestione del documento: