Investigating The data rate of Intelligent Reflecting Surface Under Different Deployments

Hassouna, Saber; Rains, James; Kazim, Jalil ur Rehman; Rehman, Masood Ur; Imran, Muhammad Ali; Abbasi, Qammer H.

doi:10.1109/ap-s/usnc-ursi47032.2022.9886560

2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (AP-S/URSI) 2022

DOI: 10.1109/ap-s/usnc-ursi47032.2022.9886560

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Investigating The data rate of Intelligent Reflecting Surface Under Different Deployments

Saber Hassouna

James Rains

Jalil ur Rehman Kazim

et al.

Abstract: There may be differences between this version and the published version. You are advised to consult the publisher's version if you wish to cite from it. https://eprints.gla.ac.uk/267949/ Deposited on: 25 Μarch 2022 Enlighten -Research publications by members of the University of Glasgow http://eprints.gla.ac.uk

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2024

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Joint passive beamforming and deployment design for active intelligent reflecting surface-assisted energy harvesting-cognitive radio sensor networks

Wang,

Zhu

2024

Sci Rep

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To prolong the network lifetime of energy harvesting-cognitive radio sensor networks (EH-CRSNs), this paper integrates active intelligent reflecting surface (IRS) to support both downlink EH and uplink data transmissions and formulates a constrained non-convex optimization problem that maximizes the net energy gain. To solve this problem, a joint passive beamforming and IRS deployment mechanism is proposed to determine the optimal deployment location of the active IRS and optimally configure the IRS reflection coefficient matrices. Specifically, the net energy gain maximization problem at a specified location is divided into two sub-problems according to its characteristics: maximizing the cumulative energy harvested by all CRSNs nodes in the downlink and minimizing the energy consumption of cluster heads in uplink data transmissions, with each sub-problem being solved independently. Furthermore, this paper explores how factors such as the number of active reflecting elements and the amplification power budget influence the optimal deployment location of the active IRS. The findings from this investigation can guide the design of active IRS-assisted EH-CRSNs under specified parameters. Simulation results confirm the aforementioned conclusions and highlight the benefits of the proposed joint mechanism in enhancing net energy gain over various benchmark mechanisms.

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Joint passive beamforming and deployment design for active intelligent reflecting surface-assisted energy harvesting-cognitive radio sensor networks

Wang,

Zhu

2024

Sci Rep

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Investigating The data rate of Intelligent Reflecting Surface Under Different Deployments

Cited by 1 publication

References 6 publications

Joint passive beamforming and deployment design for active intelligent reflecting surface-assisted energy harvesting-cognitive radio sensor networks

Joint passive beamforming and deployment design for active intelligent reflecting surface-assisted energy harvesting-cognitive radio sensor networks

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