Residential Collegefalse
IRS-Aided WPCNs: A New Optimization Framework for Dynamic IRS Beamforming
Wu, Qingqing1; Zhou, Xiaobo2,3; Chen, Wen4; Li, Jun5; Zhang, Xiuyin6
Source PublicationIEEE Transactions on Wireless Communications

In this paper, we propose a new dynamic IRS beamforming framework to boost the sum throughput of an intelligent reflecting surface (IRS) aided wireless powered communication network (WPCN). Specifically, the IRS phase-shift vectors across time and resource allocation are jointly optimized to enhance the efficiencies of both downlink wireless power transfer (DL WPT) and uplink wireless information transmission (UL WIT) between a hybrid access point (HAP) and multiple wirelessly powered devices. To this end, we first study three special cases of the dynamic IRS beamforming, namely user-adaptive IRS beamforming, UL-adaptive IRS beamforming, and static IRS beamforming, by characterizing their optimal performance relationships and proposing corresponding algorithms. Interestingly, it is rigorously proved that the latter two cases achieve the same throughput, thus helping halve the number of IRS phase shifts to be optimized and signalling overhead practically required for UL-adaptive IRS beamforming. Then, we propose a general optimization framework for dynamic IRS beamforming, which is applicable for any given number of IRS phase-shift vectors available. Despite of the non-convexity of the general problem with highly coupled optimization variables, we propose two algorithms to solve it and particularly, the low-complexity algorithm exploits the intrinsic structure of the optimal solution as well as the solutions to the cases with user-adaptive and static IRS beamforming. Simulation results validate our theoretical findings, illustrate the practical significance of IRS with dynamic beamforming for spectral and energy efficient WPCNs, and demonstrate the effectiveness of our proposed designs over various benchmark schemes.

KeywordDynamic Beamforming Intelligent Reflecting Surface Resource Allocation Wireless Powered Iot
URLView the original
Indexed BySCIE
WOS Research AreaEngineering ; Telecommunications
WOS SubjectEngineering, Electrical & Electronic ; Telecommunications
WOS IDWOS:000838503800010
Scopus ID2-s2.0-85135224078
Fulltext Access
Citation statistics
Cited Times [WOS]:6   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.The State Key Laboratory of Internet of Things for Smart City, University of Macau, Taipa, Macau, Macao
2.The Institute of Intelligent Agriculture, Anhui Agricultural University, Hefei, 230036, China
3.The School of Physics and Electronic Engineering, Fuyang Normal University, Fuyang, 236037, China
4.The Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
5.The School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China
6.The Engineering Research Center for Short-Distance Wireless Communications and Network, Ministry of Education, School of Electronic and Information Engineering, South China University of Technology, Guangzhou, 510630, China
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Wu, Qingqing,Zhou, Xiaobo,Chen, Wen,et al. IRS-Aided WPCNs: A New Optimization Framework for Dynamic IRS Beamforming[J]. IEEE Transactions on Wireless Communications,2022,21(7):4725-4739.
APA Wu, Qingqing,Zhou, Xiaobo,Chen, Wen,Li, Jun,&Zhang, Xiuyin.(2022).IRS-Aided WPCNs: A New Optimization Framework for Dynamic IRS Beamforming.IEEE Transactions on Wireless Communications,21(7),4725-4739.
MLA Wu, Qingqing,et al."IRS-Aided WPCNs: A New Optimization Framework for Dynamic IRS Beamforming".IEEE Transactions on Wireless Communications 21.7(2022):4725-4739.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Wu, Qingqing]'s Articles
[Zhou, Xiaobo]'s Articles
[Chen, Wen]'s Articles
Baidu academic
Similar articles in Baidu academic
[Wu, Qingqing]'s Articles
[Zhou, Xiaobo]'s Articles
[Chen, Wen]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Wu, Qingqing]'s Articles
[Zhou, Xiaobo]'s Articles
[Chen, Wen]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.