Battery recharging time models for reconfigurable intelligent surfaces-assisted wireless power transfer systems

Mohjazi, L. , Muhaidat, S., Abbasi, Q. H. , Imran, M. A. , Dobre, O. A. and Di Renzo, M. (2021) Battery recharging time models for reconfigurable intelligent surfaces-assisted wireless power transfer systems. IEEE Transactions on Green Communications and Networking, 6(2), pp. 1173-1185. (doi: 10.1109/TGCN.2021.3120834)

Abstract

In this paper, we develop an analytical framework for the statistical analysis of the battery recharging time (BRT) in reconfigurable intelligent surfaces (RISs)-aided wireless power transfer (WPT) systems. Specifically, we derive novel closed-form expressions for the probability density function (PDF), cumulative distribution function, and moments of the BRT of the radio frequency energy harvesting wireless nodes. Moreover, a closed-form expression of the PDF of the BRT is obtained for the special case when the RIS consists of a large number of elements. Capitalizing on the derived expressions, we offer a comprehensive treatment for the statistical characterization of the BRT and study the impact of the system and battery parameters on its performance. Our results reveal that the proposed statistical models are analytically tractable, accurate, and efficient in assessing the sustainability of RIS-assisted WPT networks and in providing key design insights for large-scale future wireless applications. For example, we demonstrate that a 4-fold reduction in the mean time of the BRT can be achieved by doubling the number of RIS elements. Monte Carlo simulation results corroborate the accuracy of the proposed theoretical framework.

• Item Type: Articles
• Additional Information: The work of M. Di Renzo was supported in part by the European Commission through the H2020 ARIADNE project under grant agreement number 871464 and through the H2020 RISE-6G project under grant agreement number 101017011.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Imran, Professor Muhammad and Abbasi, Professor Qammer and Mohjazi, Dr Lina
• Authors: Mohjazi, L., Muhaidat, S., Abbasi, Q. H., Imran, M. A., Dobre, O. A., and Di Renzo, M.
• College/School: College of Science and Engineering > School of Engineering > Systems Power and Energy
• Journal Name: IEEE Transactions on Green Communications and Networking
• Publisher: IEEE
• ISSN: 2473-2400
• ISSN (Online): 2473-2400
• Published Online: 18 October 2021
• Copyright Holders: Copyright © 2021 IEEE
• First Published: First published in IEEE Transactions on Green Communications and Networking 6(2):1173-1185
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher