Performance Evaluation of Direct-Link Backhaul for UAV-Aided Emergency Networks

Today’s wireless networks provide us reliable connectivity. However, if a disaster occurs, the whole network could be out of service and people cannot communicate. Using a fast deployable temporally network by mounting small cell base stations on unmanned aerial vehicles (UAVs) could solve the problem. Yet, this raises several challenges. We propose a capacity-deployment tool to design the backhaul network for UAV-aided networks and to evaluate the performance of the backhaul network in a realistic scenario in the city center of Ghent, Belgium. This tool assigns simultaneously resources to the ground users—access network—and to the backhaul network, taking into consideration backhaul capacity and power restrictions. We compare three types of backhaul scenarios using a 3.5 GHz link, 3.5 GHz with carrier aggregation (CA) and the 60 GHz band, considering three different types of drones. The results showed that an optimal UAV flight height (80 m) could satisfy both access and backhaul networks; however, full coverage was difficult to achieve. Finally, we discuss the influence of the flight height and the number of requesting users concerning the network performance and propose an optimal configuration and new mechanisms to improve the network capacity, based on realistic restrictions.

• Autores: Castellanos, German; Deruyck, Margot; Martens, Luc; Joseph, Wout
• Tipo de recurso: Article of investigation
• Fecha de publicación: 2019
• Institución: Escuela Colombiana de Ingeniería Julio Garavito
• Repositorio: Repositorio Institucional ECI
• Idioma: eng
• OAI Identifier: oai:repositorio.escuelaing.edu.co:001/1427
• Acceso en línea: https://repositorio.escuelaing.edu.co/handle/001/1427; https://doi.org/10.3390/s19153342
• Palabra clave: Sistemas de comunicación inalámbrica; Redes de sensores inalámbricos; Wireless communication systems; Wireless sensor networks; UABS; Backhaul; UAV; Disaster scenarios; Millimeter wave
• Rights: openAccess
• License: https://creativecommons.org/licenses/by/4.0/