Joint Beamforming Design for Hybrid RIS-Assisted mmWave ISAC System Relying on Hybrid Precoding Structure

In this article, we investigate a millimeter wave integrated sensing and communication system with aid of the hybrid reconfigurable intelligent surface (HRIS), where the dual-function radar and communication station (DFBS) applies the hybrid precoding (HP) structure. On this basis, we consider the s...

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Bibliographic Details
Published in:IEEE internet of things journal Vol. 11; no. 18; pp. 29455 - 29469
Main Authors: Hao, Wanming, Qu, Yongchao, Zhou, Shuang, Wang, Fang, Lu, Zhaoming, Yang, Shouyi
Format: Journal Article
Language:English
Published: Piscataway IEEE 15.09.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Array signal processing
Beamforming
Communication
Communications systems
Convexity
Design optimization
Design standards
Euclidean geometry
Human-robot interaction
Hybrid precoding (HP)
hybrid RIS (HRIS)
integrated sensing and communication (ISAC)
Mathematical programming
Millimeter wave communication
Millimeter waves
millimeter-wave (mmWave)
Optimization techniques
Quadratic programming
Reconfigurable intelligent surfaces
Reflection
Sensors
Signal to noise ratio
Taylor series
ISSN:2327-4662, 2327-4662
Online Access:Get full text
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Summary:In this article, we investigate a millimeter wave integrated sensing and communication system with aid of the hybrid reconfigurable intelligent surface (HRIS), where the dual-function radar and communication station (DFBS) applies the hybrid precoding (HP) structure. On this basis, we consider the sensing and communication performance, respectively, and formulate two optimization problems. One is to maximize the worst-case illumination power while ensuring the communication quality, and another is to maximize the total achievable rate while satisfying the sensing performance. To solve them, we first decouple each nonconvex problem into three subproblems via the alternative optimization technique. For the former one, we transform DFBS and HRIS beamforming optimization subproblems into the convex ones by the quadratic constrained quadratic programming (QCQP) and semidefinite program relaxation (SDR) techniques, and obtain the solutions by standard convex optimization technique. For the later one, fractional programming is applied to decouple the objective function, and then we transform DFBS and HRIS beamforming design subproblems into the convex ones by QCQP and Taylor expansion techniques, and obtain the solutions by the alternating direction method of multipliers (ADMMs). For the HP design subproblems of DFBS in both problems, a manifold optimization-alternating minimization (MO-AltMin) algorithm based on minimizing the Euclidean distance is used to obtain the solutions. Simulation results show the effectiveness of the proposed schemes.
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ISSN:2327-4662
2327-4662
DOI:10.1109/JIOT.2024.3390134