Joint Beamforming Optimization for UAV and an Active RIS-Assisted Hybrid DFRC Systems

This article investigates unmanned aerial vehicle (UAV) and an active reconfigurable intelligent surface (RIS)-assisted millimeter-wave (mmWave) dual-function radar-communication (DFRC) system. The DFRC base station (BS) employs a hybrid analog-digital (HAD) architecture. Under the constraints of th...

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Bibliographic Details
Published in:IEEE internet of things journal Vol. 12; no. 18; pp. 38059 - 38072
Main Authors: Wu, Guilu, Zhao, Xiangshuo, Jiang, Hao, Chen, Zhen
Format: Journal Article
Language:English
Published: Piscataway IEEE 15.09.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Array signal processing
Autonomous aerial vehicles
Beamforming
Constraints
dual-functional radar communication (DFRC)
hybrid beamforming (HBF)
Interference
millimeter wave (mmWave)
Millimeter wave communication
Millimeter waves
Optimization
Radar
Radar antennas
Radio frequency
reconfigurable intelligent surface (RIS)
Reconfigurable intelligent surfaces
Signal to noise ratio
Unmanned aerial vehicles
ISSN:2327-4662, 2327-4662
Online Access:Get full text
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Summary:This article investigates unmanned aerial vehicle (UAV) and an active reconfigurable intelligent surface (RIS)-assisted millimeter-wave (mmWave) dual-function radar-communication (DFRC) system. The DFRC base station (BS) employs a hybrid analog-digital (HAD) architecture. Under the constraints of the active RIS and BS power budgets, the unit-modulus analog precoder, and the desired radar beamforming pattern, we jointly optimize the BS hybrid beamforming (HBF) and active RIS beamforming to maximize the signal-to-interference-plus-noise ratio (SINR) of user. Considering the nonconvex SINR objective function and unit-modulus constraints, we propose a weighted minimum mean square error (WMMSE) method based on the penalty dual decomposition (PDD) framework and alternating optimization (AO). For the active RIS beamforming design, we introduce the semidefinite relaxation (SDR) method and a majorization-minimization (MM) method. Finally, the simulation results demonstrate the potential of active RIS in DFRC systems compared to the passive RIS.
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ISSN:2327-4662
2327-4662
DOI:10.1109/JIOT.2025.3585202