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Amplitude-Based Sequential Optimization of Energy Harvesting with Reconfigurable Intelligent Surfaces
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Communication Systems, CoS.ORCID iD: 0000-0003-2834-0317
Ericsson, Global AI Accelerator (GAIA) unit, Sweden.
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Communication Systems, CoS.ORCID iD: 0000-0002-5954-434x
2023 (English)In: Conference Record of the 57th Asilomar Conference on Signals, Systems and Computers, ACSSC 2023, Institute of Electrical and Electronics Engineers (IEEE) , 2023, p. 480-483Conference paper, Published paper (Refereed)
Abstract [en]

Reconfigurable Intelligent Surfaces (RISs) have gained immense popularity in recent years because of their ability to improve wireless coverage and their flexibility to adapt to the changes in a wireless environment. These advantages are due to RISs' ability to control and manipulate radio frequency (RF) wave propagation. RISs may be deployed in inaccessible locations where it is difficult or expensive to connect to the power grid. Energy harvesting (EH) can enable the RIS to self-sustain its operations without relying on external power sources. In this paper, we consider the problem of energy harvesting for RISs in the absence of coordination with the ambient RF source. We consider both direct and indirect EH scenarios and show that the same mathematical model applies to them. We propose a sequential phase-alignment algorithm that maximizes the received power based on only power measurements. We prove the convergence of the proposed algorithm to the optimal value under specific circumstances. Our simulation results show that the proposed algorithm converges to the optimal solution in a few iterations and outperforms the random phase update method in terms of the number of required measurements.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2023. p. 480-483
Keywords [en]
Energy harvesting, phased array, reconfigurable intelligent surface, zero-energy devices
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:kth:diva-350167DOI: 10.1109/IEEECONF59524.2023.10476941ISI: 001207755100086Scopus ID: 2-s2.0-85190389639OAI: oai:DiVA.org:kth-350167DiVA, id: diva2:1883237
Conference
57th Asilomar Conference on Signals, Systems and Computers, ACSSC 2023, October 29 - November 1, 2023, Pacific Grove, United States of America
Note

Part of ISBN 9798350325744

QC 20241023

Available from: 2024-07-09 Created: 2024-07-09 Last updated: 2024-10-23Bibliographically approved

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Tavana, MortezaBjörnson, Emil

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