Robust Transmission Design for IRS-Assisted Secure Wireless-Powered Communication Network With Hardware Impairments

In this paper, a robust transmission design is investigated for an intelligent reflecting surface (IRS)-assisted secure wireless powered communication network (WPCN) in the presence of hardware impairments at the transceiver. An IRS is deployed to enhance the efficiency of downlink (DL) wireless energy transfer (WET) and the security of uplink (UL) wireless information transfer (WIT). To maximize the secrecy throughput, the DL and UL time allocation, the transmit beamforming vector at the power station (PS), the receive beamforming vector at the access point (AP), and phase-shifts of IRS in DL and UL are jointly optimized. To handle the resulting non-convex optimization problem, an efficient algorithm based on block coordinate descent (BCD) is developed to iteratively update the optimization variables. Specifically, the closed-form solution of the receive beamforming vector is derived and the transmit beamforming vector can be obtained by the successive convex approximation (SCA) method. Then, the semidefinite relaxation (SDR) method is used to solve the corresponding IRS phase-shifts optimization sub-problems in DL and UL. Simulation results unveil that simultaneously optimizing the IRS phase-shifts in DL and UL can largely compensate for the hardware impairments compared to the schemes that optimize either DL/UL alone. Furthermore, the proposed robust transmission design scheme achieves higher performance improvement compared to the non-robust design which ignores the impact of hardware impairments.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-04-15
DOI
https://doi.org/10.1109/jiot.2025.3560827
Primary Topic
Energy Harvesting in Wireless Networks
Type
article
Field-Weighted Citation Impact
0.00

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article

Robust Transmission Design for IRS-Assisted Secure Wireless-Powered Communication Network With Hardware Impairments

Shuai Han, Chenyu Wu, Chenguang He, Yuanwei Liu et al.
IEEE Internet of Things Journal
Energy Harvesting in Wireless Networks
article

Robust Transmission Design for IRS-Assisted Secure Wireless-Powered Communication Network With Hardware Impairments

Shuai Han, Chenyu Wu, Chenguang He, Yuanwei Liu, Jing Xu
article en

Abstract

In this paper, a robust transmission design is investigated for an intelligent reflecting surface (IRS)-assisted secure wireless powered communication network (WPCN) in the presence of hardware impairments at the transceiver. An IRS is deployed to enhance the efficiency of downlink (DL) wireless energy transfer (WET) and the security of uplink (UL) wireless information transfer (WIT). To maximize the secrecy throughput, the DL and UL time allocation, the transmit beamforming vector at the power station (PS), the receive beamforming vector at the access point (AP), and phase-shifts of IRS in DL and UL are jointly optimized. To handle the resulting non-convex optimization problem, an efficient algorithm based on block coordinate descent (BCD) is developed to iteratively update the optimization variables. Specifically, the closed-form solution of the receive beamforming vector is derived and the transmit beamforming vector can be obtained by the successive convex approximation (SCA) method. Then, the semidefinite relaxation (SDR) method is used to solve the corresponding IRS phase-shifts optimization sub-problems in DL and UL. Simulation results unveil that simultaneously optimizing the IRS phase-shifts in DL and UL can largely compensate for the hardware impairments compared to the schemes that optimize either DL/UL alone. Furthermore, the proposed robust transmission design scheme achieves higher performance improvement compared to the non-robust design which ignores the impact of hardware impairments.

IEEE Internet of Things JournalVol. 12(13)
Harbin Institute of Technology (CN), University of Hong Kong (HK)
National Natural Science Foundation of China, China Postdoctoral Science Foundation
Affordable and clean energy
Openalex Percentile: Top 94%
Energy Harvesting in Wireless Networks
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