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Please use this identifier to cite or link to this item: https://www.repositorio.mar.mil.br/handle/ripcmb/844794
Title: 5G inspired method for ranging of UAVs in swarming composition
Authors: Martins, Madjer de Andrade
metadata.dc.contributor.advisor: Garren, David A.
Keywords: 5th Generation Mobile Networks
Swarm Drones
5G Network
Zadoff-Chu Sequence
DGPM knowledge areas: Telecomunicações
Issue Date: Sep-2021
Publisher: Naval Postgraduate School (NPS)
Citation: MARTINS, Madjer de Andrade. 5G inspired method for ranging of UAVs in swarming composition. 88 f. 2021. Thesis (Master of Science in Eletrical Engineering) - Naval Postgraduate School, California USA, 2021.
Abstract: The employment of unmanned aerial vehicles is currently a fact in modern warfare. The benefit of using drones as a swarm, working together to accomplish a task, will help save lives; however, the communication among drones within a swarm is a challenge with the available technology due mainly to the power requirements to operate in a small device. Inspired by the massive machine-type communication 5th generation mobile networks, this work offers a novel method of identification and ranging for drones in swarm. The 5G communication channel’s preamble with a Zadoff-Chu (ZC) sequence is expected to provide low power and less interference between devices and yet yield good mean-square error results when a matched filter is applied. Simulations considering different numbers of drones within a swarm embedded in noisy and Doppler-affected environments demonstrate promising results even in poor scenarios with small signal-to-noise ratio and high Doppler frequency shift, especially when the batch of ZC sequences’ root indexes are selected into a special group.
Access: Open access
URI: http://www.repositorio.mar.mil.br/handle/ripcmb/844794
Type: Master thesis
Appears in Collections:Telecomunicações: Coleção de Dissertações

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