Joint Optimization of Power Allocation and Beamforming for UAV-RIS Communication System
Authors: Guo, X., Liu, L., Zhang, J. and Chen, S.
Journal: IEEE Wireless Communications Letters
Volume: 14
Issue: 6
Pages: 1733-1737
eISSN: 2162-2345
ISSN: 2162-2337
DOI: 10.1109/LWC.2025.3554304
Abstract:This letter considers the communication system assisted by a fixed-trajector uncrewed aerial vehicle (UAV), which is equipped with a reconfigurable intelligent surface (RIS). For this UAV-RIS assisted system, we jointly optimize the power allocation and active beamforming at the base station (BS) and the passive beamforming at the RIS, by a novel phase block coordinate descent algorithm framework aimed at maximizing the system sum-rate. Specifically, the joint optimization problem is decomposed into two phases, and we propose two optimization algorithms: one for BS power allocation using fractional programming (FP) and the other for jointly optimizing active and passive beamforming using FP-manifold, which alternately optimize two phases. Simulation results not only highlight the rapid convergence and evident superiority of our proposed framework but also reveal that the optimal UAV-RIS placement is related to the flight height.
https://eprints.bournemouth.ac.uk/40941/
Source: Scopus
Joint Optimization of Power Allocation and Beamforming for UAV-RIS Communication System
Authors: Guo, X., Liu, L., Zhang, J. and Chen, S.
Journal: IEEE WIRELESS COMMUNICATIONS LETTERS
Volume: 14
Issue: 6
Pages: 1733-1737
eISSN: 2162-2345
ISSN: 2162-2337
DOI: 10.1109/LWC.2025.3554304
https://eprints.bournemouth.ac.uk/40941/
Source: Web of Science (Lite)
Joint Optimization of Power Allocation and Beamforming for UAV-RIS Communication System
Authors: Guo, X., Liu, L., Zhang, J. and Chen, S.
Journal: IEEE Wireless Communications Letters
Volume: 14
Issue: 6
Pages: 1733-1737
ISSN: 2162-2337
Abstract:This paper considers the communication system assisted by a fixed-trajectory unmanned aerial vehicle (UAV), which is equipped with a reconfigurable intelligent surface (RIS). For this UAV-RIS assisted system, we jointly optimize the power allocation and active beamforming at the base station (BS) and the passive beamforming at the RIS, by a novel phase block coordinate descent algorithm framework aimed at maximizing the system sum-rate. Specifically, the joint optimization problem is decomposed into two phases, and we propose two optimization algorithms: one for BS power allocation using fractional programming (FP) and the other for jointly optimizing active and passive beamforming using FP-manifold, which alternately optimize two phases. Simulation results not only highlight the rapid convergence and evident superiority of our proposed framework but also reveal that the optimal UAV-RIS placement is related to the flight height.
https://eprints.bournemouth.ac.uk/40941/
Source: BURO EPrints