Dynamic algorithm for interference mitigation between cells in networks operating in the 250 MHz band

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorCarrillo Melgarejo, Dick-
Autor(es): dc.creatorCosta Filho, Luiz Quirino Rezende da-
Autor(es): dc.creatorMedeiros, Álvaro Augusto Machado de-
Autor(es): dc.creatorLorena Neto, Carlos-
Autor(es): dc.creatorFigueiredo, Fabricio Lira-
Autor(es): dc.creatorZegarra Rodríguez, Demóstenes-
Data de aceite: dc.date.accessioned2026-02-09T11:12:06Z-
Data de disponibilização: dc.date.available2026-02-09T11:12:06Z-
Data de envio: dc.date.issued2022-10-24-
Data de envio: dc.date.issued2022-10-24-
Data de envio: dc.date.issued2022-03-
Fonte completa do material: dc.identifierhttps://repositorio.ufla.br/handle/1/55339-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1135825-
Descrição: dc.descriptionThe growing demand for Internet of Things (IoT) applications in agribusiness increases the necessity of reliable and secure connectivity in rural areas. Thus, in the particular case of Brazil, some initiatives aim to take advantage of frequency bands dedicated to limited private services. For instance, cellular networks based on orthogonal frequency-division multiple access (OFDMA) in 250 MHz bands require specialized adaptations because the interference between cells increases when these systems operate in the Very High Frequency (VHF) band. This work presents an analysis based on a reliable simulation of interference mitigation in OFDMA systems at 250 MHz using a network simulator. The simulator is calibrated with data obtained in the field by an extensive and rigorous drive test. Therefore, the analysis is based on a comparison of traditional frequency reuse schemes with a machine learning approach based on deep reinforcement learning (DRL) to reduce inter-cell interference. The numerical results indicate that the DRL approach outperforms the traditional frequency reuse (FR) schemes in four different typical agribusiness scenarios.-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Publicador: dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)-
Direitos: dc.rightsacesso aberto-
Direitos: dc.rightshttp://creativecommons.org/licenses/by/4.0/-
Direitos: dc.rightshttp://creativecommons.org/licenses/by/4.0/-
???dc.source???: dc.sourceIEEE Access-
Palavras-chave: dc.subjectInternet of Things-
Palavras-chave: dc.subjectFrequency reuse-
Palavras-chave: dc.subjectDeep reinforcement learning-
Palavras-chave: dc.subjectCustomized cellular networks-
Palavras-chave: dc.subjectBroadband communication-
Palavras-chave: dc.subjectInternet das coisas-
Palavras-chave: dc.subjectReutilização de frequência-
Palavras-chave: dc.subjectAprendizagem por reforço profundo-
Palavras-chave: dc.subjectBanda larga-
Palavras-chave: dc.subjectAnálise de discurso-
Título: dc.titleDynamic algorithm for interference mitigation between cells in networks operating in the 250 MHz band-
Tipo de arquivo: dc.typeArtigo-
Aparece nas coleções:Repositório Institucional da Universidade Federal de Lavras (RIUFLA)

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