2018 IEEE International Conference on Environmental Engineering (EE) 2018
DOI: 10.1109/ee1.2018.8385250
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Energy-Efficient Mission Planning of UAVs for 5G Coverage in Rural Zones

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Cited by 41 publications
(37 citation statements)
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“…In [118], UAV mission planning is performed, with the objective of ensuring coverage while minimizing energy consumption. UAVs stay at neighboring ground sites to recharge their batteries as in [115,116], and then move to target areas to provide 5G coverage. The energy minimization problem is solved using Genetic Algorithms, and results are shown to compare favorably to other works in the literature [118].…”
Section: ) 5g Small Cellsmentioning
confidence: 99%
“…In [118], UAV mission planning is performed, with the objective of ensuring coverage while minimizing energy consumption. UAVs stay at neighboring ground sites to recharge their batteries as in [115,116], and then move to target areas to provide 5G coverage. The energy minimization problem is solved using Genetic Algorithms, and results are shown to compare favorably to other works in the literature [118].…”
Section: ) 5g Small Cellsmentioning
confidence: 99%
“…2) Using UAVs with 5G: In [115,116], UAVs are used to provide access to rural areas, rather than being used for backhaul transport. Each UAV is assumed to be a moving 5G BS, covering a given area.…”
Section: A 5g Networkmentioning
confidence: 99%
“…Thus, the number of UAVs is twice the number of covered areas. This approach was found in [87,88] to be more cost effective than deploying a network consisting solely of fixed ground BS sites. It was also shown to lead to economically feasible deployments with subscription fees of around 20 Euros/month in certain rural areas [89].…”
Section: A 5g Networkmentioning
confidence: 99%
“…In [90], UAV mission planning is performed, with the objective of ensuring coverage while minimizing energy consumption. UAVs stay at neighboring ground sites to recharge their batteries as in [87,88], and then move to target areas to provide 5G coverage. The energy minimization problem is solved using Genetic Algorithms, and results are shown to compare favorably to other works in the literature [90].…”
Section: A 5g Networkmentioning
confidence: 99%