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dc.contributor.author | Bernabè, Matteo | es_ES |
dc.contributor.author | López-Pérez, David | es_ES |
dc.contributor.author | Piovesan, Nicola | es_ES |
dc.contributor.author | Geraci, Giovanni | es_ES |
dc.contributor.author | Gesbert, David | es_ES |
dc.date.accessioned | 2024-09-09T18:09:36Z | |
dc.date.available | 2024-09-09T18:09:36Z | |
dc.date.issued | 2024 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/207820 | |
dc.description.abstract | [EN] In this article, we introduce a novel approach for enhancing cellular connectivity for unmanned aerial vehicles (UAVs) on aerial highways via terrestrial 5G networks. Owing to their ability to navigate 3D space, UAVs may experience favourable channel gains across multiple network cells; thus, from a network operator's perspective, selecting serving cells that maximize UAV capacity is not straightforward. Merely considering conventional metrics like reference signal received power (RSRP) may lead to selecting cells that offer high power but are inefficient in multiplexing UAVs, leading to possible reduced data rate performance. To tackle this problem, we propose a novel 5G synchronization signal block (SSB) beams planning solution to strategically control the UAVs cell association and maximize UAVs capacity without affecting terrestrial users. To solve the associated NP-hard problem, we propose a heuristic solution based on a novel metric that captures the multiplexing capability, average channel quality gain, and interference. Leveraging our proposed metric, we first optimally split the aerial highway and define serving cells, and then optimally select SSB beams and their transmitting power to ensure coverage from the previously defined serving cells set. Results indicate that our solution significantly improves the UAV data rate performance on aerial highways across different network scenarios and traffic conditions without impacting terrestrial users. | es_ES |
dc.description.sponsorship | This work was supported in part by the Generalitat Valenciana, Spain, through CIDEGENT PlaGenT under Grant CIDEXG/2022/17 and Project iTENTE; in part by the Spanish State Research Agency under Grant PID2021-123999OB-I00, Grant CEX2021-001195-M, and Grant CNS2023-145384; in part by the UPF-Fractus Chair on Tech Transfer and 6G; and in part by the Spanish Ministry of Economic Affairs and Digital Transformation and the European Union NextGenerationEU. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | IEEE Communications Society | es_ES |
dc.relation.ispartof | IEEE Open Journal of the Communications Society | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | 3D network | es_ES |
dc.subject | 5G | es_ES |
dc.subject | SSB beam planning | es_ES |
dc.subject | UAV, Aerial highways | es_ES |
dc.subject | Cell association | es_ES |
dc.subject | Drone corridors | es_ES |
dc.subject | MMIMO | es_ES |
dc.title | Massive MIMO for Aerial Highways: Enhancing Cell Selection via SSB Beams Optimization | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1109/OJCOMS.2024.3418339 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-123999OB-I00/ES/HACIA EL DESPLIEGUE DE REDES NO TERRESTRES/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/GVA//CIDEXG%2F2022%2F17//iTENTE/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI//CEX2021-001195-M/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI//CNS2023-145384/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Instituto Universitario de Telecomunicación y Aplicaciones Multimedia - Institut Universitari de Telecomunicacions i Aplicacions Multimèdia | es_ES |
dc.description.bibliographicCitation | Bernabè, M.; López-Pérez, D.; Piovesan, N.; Geraci, G.; Gesbert, D. (2024). Massive MIMO for Aerial Highways: Enhancing Cell Selection via SSB Beams Optimization. IEEE Open Journal of the Communications Society. 5:3975-3996. https://doi.org/10.1109/OJCOMS.2024.3418339 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1109/OJCOMS.2024.3418339 | es_ES |
dc.description.upvformatpinicio | 3975 | es_ES |
dc.description.upvformatpfin | 3996 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 5 | es_ES |
dc.identifier.eissn | 2644-125X | es_ES |
dc.relation.pasarela | S\525056 | es_ES |
dc.contributor.funder | European Commission | es_ES |
dc.contributor.funder | Generalitat Valenciana | es_ES |
dc.contributor.funder | Universitat Pompeu Fabra | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |