UAV Swarm-Enabled Aerial Reconfigurable Intelligent Surface: Modeling, Analysis, and Optimization

Reconfigurable intelligent surface (RIS) offers tremendous spectrum-and-energy efficiency in wireless networks. With the agility and mobility of an unmanned aerial vehicle (UAV), RIS can be mounted on a UAV to enable three-dimensional (3D) signal reflections, reliable air-ground connections, and hig...

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Bibliographic Details
Published in:IEEE transactions on communications 2023-06, Vol.71 (6), p.3621-3636
Main Authors: Shang, Bodong, Bentley, Elizabeth Serena, Liu, Lingjia
Format: Article
Language:English
Subjects:
Analytical models
Array signal processing
Autonomous aerial vehicles
Beamforming
Communications systems
Downlink
line-of-sight (LoS) connection
multiple-input-single-output (MISO) transmission
Multiplexing
non-line-of-sight (NLoS) connection
Optimization
Placement
reconfigurable intelligent surface (RIS)
Reconfigurable intelligent surfaces
Reflection
Three-dimensional displays
Unmanned aerial vehicle (UAV)
Unmanned aerial vehicles
Wireless networks
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Summary:Reconfigurable intelligent surface (RIS) offers tremendous spectrum-and-energy efficiency in wireless networks. With the agility and mobility of an unmanned aerial vehicle (UAV), RIS can be mounted on a UAV to enable three-dimensional (3D) signal reflections, reliable air-ground connections, and higher configuration flexibility. However, the scalability of the aperture gain and the spatial multiplexing could not be guaranteed in a single UAV-enabled aerial RIS due to UAV's limited payload and line-of-sight-dominated air-ground connection. In this paper, we study a UAV swarm-enabled aerial RIS (SARIS)-assisted downlink communication system. The objective of the considered SARIS system is to maximize the weighted sum-rate of ground users by designing the transmit beamforming at the base station (BS), the phase shifts of SARIS reflecting elements, and SARIS 3D placement. For joint BS and SARIS beamforming design, we introduce two beamforming schemes with low computational complexity. For SARIS placement design, the optimal SARIS 3D position is obtained by leveraging the tools from stochastic geometry and considering the distributions of ground users. Simulation results confirm the validity of the analytical derivations. In particular, the SARIS placement plays a vital role in the system performance when the distances between users and the BS increase.
ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2022.3173369