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dc.contributor.advisorGarren, David A.-
dc.contributor.authorMartins, Madjer de Andrade-
dc.date.accessioned2022-07-05T18:13:38Z-
dc.date.available2022-07-05T18:13:38Z-
dc.date.issued2021-09-
dc.identifier.citationMARTINS, 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.pt_BR
dc.identifier.urihttp://www.repositorio.mar.mil.br/handle/ripcmb/844794-
dc.description.abstractThe 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.pt_BR
dc.language.isoengpt_BR
dc.publisherNaval Postgraduate School (NPS)pt_BR
dc.rightsopenAccesspt_BR
dc.subject5th Generation Mobile Networkspt_BR
dc.subjectSwarm Dronespt_BR
dc.subject5G Networkpt_BR
dc.subjectZadoff-Chu Sequencept_BR
dc.title5G inspired method for ranging of UAVs in swarming compositionpt_BR
dc.typemasterThesispt_BR
dc.location.countryEUApt_BR
dc.subject.dgpmTelecomunicaçõespt_BR
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