Intelligent UAV Deployment for a Disaster-Resilient Wireless Network; Sensors; Vol. 20, iss. 21

Intelligent UAV Deployment for a Disaster-Resilient Wireless Network; Sensors; Vol. 20, iss. 21

Bibliographic Details
Parent link:Sensors
Vol. 20, iss. 21.— 2020.— [6140, 18 p.]
Corporate Author: Национальный исследовательский Томский политехнический университет Инженерная школа информационных технологий и робототехники Научно-образовательный центр "Автоматизация и информационные технологии"
Other Authors: Hydher H. Hassaan, Dzhayakodi (Jayakody) Arachshiladzh D. N. K. Dushanta Nalin Kumara, Hemachandra K. Kasun, Samarasinghe T. Tharaka
Summary:Title screen
Deployment of unmanned aerial vehicles (UAVs) as aerial base stations (ABSs) has been considered to be a feasible solution to provide network coverage in scenarios where the conventional terrestrial network is overloaded or inaccessible due to an emergency situation. This article studies the problem of optimal placement of the UAVs as ABSs to enable network connectivity for the users in such a scenario. The main contributions of this work include a less complex approach to optimally position the UAVs and to assign user equipment (UE) to each ABS, such that the total spectral efficiency (TSE) of the network is maximized, while maintaining a minimum QoS requirement for the UEs. The main advantage of the proposed approach is that it only requires the knowledge of UE and ABS locations and statistical channel state information. The optimal 2-dimensional (2D) positions of the ABSs and the UE assignments are found using K-means clustering and a stable marriage approach, considering the characteristics of the air-to-ground propagation channels, the impact of co-channel interference from other ABSs, and the energy constraints of the ABSs. Two approaches are proposed to find the optimal altitudes of the ABSs, using search space constrained exhaustive search and particle swarm optimization (PSO). The numerical results show that the PSO-based approach results in higher TSE compared to the exhaustive search-based approach in dense networks, consuming similar amount of energy for ABS movements. Both approaches lead up to approximately 8-fold energy savings compared to ABS placement using naive exhaustive search.
Language:English
Published: 2020
Subjects:
электронный ресурс
труды учёных ТПУ
aerial base station
average spectral efficiency
interference mitigation
particle swarm optimization
unmanned aerial vehicles
Online Access:http://earchive.tpu.ru/handle/11683/64782
https://doi.org/10.3390/s20216140
Format: Electronic Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=663134

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