Joint Power Allocation and Passive Beamforming Design for IRS-Assisted Physical-Layer Service Integration

Intelligent reflecting surface (IRS) has emerged as an appealing solution to enhance wireless communication performance by reconfiguring the wireless propagation environment. In this paper, we propose to apply IRS to the physical-layer service integration (PHY-SI) system, where a single-antenna acce...

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Bibliographic Details
Published in:IEEE transactions on wireless communications Vol. 20; no. 11; pp. 7286 - 7301
Main Authors: Ning, Boyu, Chen, Zhi, Tian, Zhongbao, Wang, Xiaomei, Pan, Cunhua, Fang, Jun, Li, Shaoqian
Format: Journal Article
Language:English
Published: New York IEEE 01.11.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Antennas
Approximation algorithms
Array signal processing
Beamforming
Convexity
Intelligent reflecting surface
Messages
Multicast algorithms
Multicasting
Optimization
Pareto optimization
physical layer service integration
Resource management
secrecy rate region
Wireless communication
Wireless communications
wiretap channel
ISSN:1536-1276, 1558-2248
Online Access:Get full text
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Summary:Intelligent reflecting surface (IRS) has emerged as an appealing solution to enhance wireless communication performance by reconfiguring the wireless propagation environment. In this paper, we propose to apply IRS to the physical-layer service integration (PHY-SI) system, where a single-antenna access point (AP) integrates two sorts of service messages, i.e., multicast message and confidential message, via superposition coding to serve multiple single-antenna users. Our goal is to optimize the power allocation (for transmitting different messages) at the AP and the passive beamforming at the IRS to maximize the achievable secrecy rate region. To this end, we formulate this problem as a bi-objective optimization problem, which is shown equivalent to a secrecy rate maximization problem subject to the constraints on the quality of multicast service. Due to the non-convexity of this problem, we propose two customized algorithms to obtain its high-quality suboptimal solutions, thereby approximately characterizing the secrecy rate region. The resulting performance gap with the globally optimal solution is analyzed. Furthermore, we provide theoretical analysis to unveil the impact of IRS beamforming on the performance of PHY-SI. Numerical results demonstrate the advantages of leveraging IRS in improving the performance of PHY-SI and also validate our theoretical analysis.
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ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2021.3082530