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Joint Beamforming and BS Selection for Energy-Efficient Communications via Aerial-RIS

Quispe, Jaime ; Maciel, Tarcisio Ferreira ; Silva, Yuri Carvalho Barbosa ; Klein, Anja (2021)
Joint Beamforming and BS Selection for Energy-Efficient Communications via Aerial-RIS.
IEEE Global Communications Conference 2021. virtual Conference and Madrid, Spain (07.-11.12.2021)
doi: 10.1109/GCWkshps52748.2021.9681981
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Cooperative BS transmission via unmanned aerial vehicles (UAVs)-airborne reconfigurable intelligent surface (RIS), also known as aerial-RIS, is a promising solution for providing connectivity in emergency areas where network access is unavailable. The RIS requires low power in reflecting the impinging base station (BS) signals towards the direction of the user equipment (UE), and the cooperative transmission can provide a more stable connection that guarantees quality-of-service (QoS). In this work, we investigate the energy efficiency (EE) maximization of a multiple-BS single-UE single-aerial-RIS setup and the usefulness of cooperation to prevent outages. The BSs can be turned either on or off depending on their contribution to the EE, and the system is subject to QoS, power, capacity, and RIS specific constraints. We formulate a problem that jointly optimizes the selection of the BSs and the beamforming weights of BSs and RIS, and solve it with a Branch-Reduce-and-Bound (BRnB) algorithm that uses monotonic optimization and semidefinite relaxation steps. Simulation results for an illustrative setup show that the aerial-RIS increases the EE by 50% when doubling the number of its elements and cooperative aerial-RIS transmissions help to solve outages of single-BS cases.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2021
Autor(en): Quispe, Jaime ; Maciel, Tarcisio Ferreira ; Silva, Yuri Carvalho Barbosa ; Klein, Anja
Art des Eintrags: Bibliographie
Titel: Joint Beamforming and BS Selection for Energy-Efficient Communications via Aerial-RIS
Sprache: Englisch
Publikationsjahr: 12 Dezember 2021
Verlag: IEEE
Buchtitel: IEEE Globecom Workshops (GC Wkshps): Proceedings
Veranstaltungstitel: IEEE Global Communications Conference 2021
Veranstaltungsort: virtual Conference and Madrid, Spain
Veranstaltungsdatum: 07.-11.12.2021
DOI: 10.1109/GCWkshps52748.2021.9681981
Kurzbeschreibung (Abstract):

Cooperative BS transmission via unmanned aerial vehicles (UAVs)-airborne reconfigurable intelligent surface (RIS), also known as aerial-RIS, is a promising solution for providing connectivity in emergency areas where network access is unavailable. The RIS requires low power in reflecting the impinging base station (BS) signals towards the direction of the user equipment (UE), and the cooperative transmission can provide a more stable connection that guarantees quality-of-service (QoS). In this work, we investigate the energy efficiency (EE) maximization of a multiple-BS single-UE single-aerial-RIS setup and the usefulness of cooperation to prevent outages. The BSs can be turned either on or off depending on their contribution to the EE, and the system is subject to QoS, power, capacity, and RIS specific constraints. We formulate a problem that jointly optimizes the selection of the BSs and the beamforming weights of BSs and RIS, and solve it with a Branch-Reduce-and-Bound (BRnB) algorithm that uses monotonic optimization and semidefinite relaxation steps. Simulation results for an illustrative setup show that the aerial-RIS increases the EE by 50% when doubling the number of its elements and cooperative aerial-RIS transmissions help to solve outages of single-BS cases.

Freie Schlagworte: emergenCITY_KOM
Fachbereich(e)/-gebiet(e): 18 Fachbereich Elektrotechnik und Informationstechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik > Kommunikationstechnik
LOEWE
LOEWE > LOEWE-Zentren
LOEWE > LOEWE-Zentren > emergenCITY
Hinterlegungsdatum: 15 Feb 2022 10:04
Letzte Änderung: 26 Aug 2022 10:12
PPN:
Projekte: BMBF Open6GHub, DAAD PPP Brasilien
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