Narrowband IoT Networks with Unmanned Aerial Base Stations

Wu, Qinlin (2020) Narrowband IoT Networks with Unmanned Aerial Base Stations. [Laurea magistrale], Università di Bologna, Corso di Studio in Telecommunications engineering [LM-DM270], Documento full-text non disponibile
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Abstract

UAV is widely used in civil applications such as environmental hazards monitoring, traffic management and pollution monitoring, all of those contribute to smart city development. Thanks to its high mobility and feasibility, UAVs can be employed as a base station, gathering data from IoT devices distribute in a certain area during its flight. In this case, an appropriate trajectory and suitable parameters set is necessary to achieve better performance. This thesis studies a scenario of NB-IoT machine-type communication network served by an unmanned aerial base station (UAB). In this scenario, the user devices are deployed with Tomas Cluster Process (TCP)[19]. Some of the nodes are named parent nodes and generated with Poisson Point Process (PPP). One single UAB is employed and its trajectory is predefined with a Travelling Salesman Problem model among the parent nodes. All the devices only generate one data packet for UL, whose activation time and expiration time is considered. Due to NB-IoT protocols, the number of resource units available on NPUSCH and the data rate for IoT devices is constrained. This study makes the network throughput and the number of users served as the main basis of performance evaluation, the variation of UAB speed, NPRACH periodicity, deployment variance, and size of the data packet as influencing factors. Finally, we present an analysis of how these parameters affect the overall performance and how the optimal configuration may be chosen according to arbitrary criteria.

Abstract
Tipologia del documento
Tesi di laurea (Laurea magistrale)
Autore della tesi
Wu, Qinlin
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Ordinamento Cds
DM270
Parole chiave
NB-IoT,UAB,machine-type communications
Data di discussione della Tesi
9 Ottobre 2020
URI

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