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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.
In: IEEE Globecom Workshops (GC Wkshps): Proceedings,
IEEE, IEEE Global Communications Conference 2021, virtual Conference and Madrid, Spain, 07.-11.12.2021, ISBN 978-1-6654-2390-8,
DOI: 10.1109/GCWkshps52748.2021.9681981,
[Conference or Workshop Item]

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.

Item Type: Conference or Workshop Item
Erschienen: 2021
Creators: Quispe, Jaime ; Maciel, Tarcisio Ferreira ; Silva, Yuri Carvalho Barbosa ; Klein, Anja
Title: Joint Beamforming and BS Selection for Energy-Efficient Communications via Aerial-RIS
Language: English
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.

Book Title: IEEE Globecom Workshops (GC Wkshps): Proceedings
Publisher: IEEE
ISBN: 978-1-6654-2390-8
Uncontrolled Keywords: emergenCITY_KOM
Divisions: 18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications
18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications > Communications Engineering
LOEWE
LOEWE > LOEWE-Zentren
LOEWE > LOEWE-Zentren > emergenCITY
Event Title: IEEE Global Communications Conference 2021
Event Location: virtual Conference and Madrid, Spain
Event Dates: 07.-11.12.2021
Date Deposited: 15 Feb 2022 10:04
DOI: 10.1109/GCWkshps52748.2021.9681981
PPN:
Projects: BMBF Open6GHub, DAAD PPP Brasilien
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