Jointly Active and Passive Beamforming Designs for IRS-Empowered WPCN

Zheng Chu, Pei Xiao, De Mi, Cheng Yin, Wanming Hao, Wei Liu, Arismar Cerqueira Sodre

Research output: Journal PublicationArticlepeer-review


This article studies an intelligent reflecting surface (IRS)-empowered wireless-powered communication network (WPCN) in Internet of Things (IoT) networks. In particular, a power station (PS) with multiple antennas uses energy beamforming to enable wireless charging to multiple IoT devices, in the downlink wireless energy transfer (WET) phase; then, during the uplink wireless information transfer (WIT) phase, these IoT devices utilize the harvested energy to concurrently transmit their individual information signal to a multiantenna access point (AP), which equips with multiuser decomposition (MUD) techniques to reconstruct the IoT devices' signal. An IRS is deployed to improve the energy collection and information transmission capabilities in the WET and WIT phases, respectively. To examine the performance of the system under study, we maximize the sum throughput with the aim of jointly designing the optimal solutions for the active PS energy beamforming, AP receive beamforming, passive IRS beamforming, and time scheduling. Due to the multiple coupled variables, the resulting formulation is nonconvex, and a two-level scheme to solve the problem is proposed. At the outer level, a 1-D search method is applied to find the optimal time scheduling, while at the inner level, an iterative block coordinate descent (BCD) algorithm is proposed to design the optimal receive beamforming, energy beamforming, and IRS phase shifts. In particular, the receive beamforming part is designed by considering the equivalence between sum rate maximization and sum mean square error (MSE) minimization, thereby deriving a closed-form solution. Furthermore, we alternately optimize the energy beamforming and IRS phase shifts using Lagrange dual transformation (LDT), quadratic transformation (QT), and alternating direction method of multipliers (ADMMs) methods. Finally, numerical results are presented to showcase the performance of the proposed solution and highlight its advantages compared to some typical benchmark schemes.

Original languageEnglish
Pages (from-to)11579-11592
Number of pages14
JournalIEEE Internet of Things Journal
Issue number7
Publication statusPublished - 1 Apr 2024
Externally publishedYes


  • Alternating direction method of multipliers (ADMMs)
  • Lagrange dual transformation (LDT)
  • intelligent reflecting surface (IRS)
  • mean square error (MSE)
  • quadratic transformation (QT)
  • wireless-powered communication networks (WPCNs)

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing
  • Hardware and Architecture
  • Computer Networks and Communications
  • Computer Science Applications


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