Exploiting Intelligent Reflecting Surface for Wireless Power Transfer via Optimization and Deep Learning Approaches

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Published: Oct 28, 2023
DOI: https://doi.org/10.37936/ecti-eec.2023213.251465
Keywords:
Wireless Power Transfer Intelligent Reflect- ing Surface Successive Convex Approximation Deep Learning Semidefinite Relaxation

Main Article Content

Pham Viet Tuan
Vinh Anh Nghiem Quan
Pham Ngoc Son
Sang Quang Nguyen
Pham Viet Hung

Abstract

In this paper, the wireless power transfer system with intelligent reflecting surface (IRS) assistance is studied to maximize the total harvested power at multiple users. The near optimal IRS phase shifts are obtained by two methods of successive convex approximation (SCA) and deep learning techniques. In the optimization method (IRS-OPT), we combine SCA technique with semidefinite relaxation to find the suboptimal solution with high harvested power performance. In the deep learning method (IRS-DL), the deep neutral network is proposed to learn the harvested power maximization via channel information. The numerical evaluations show that the IRS-OPT achieves the higher result while the IRS-DL provides the solution with almost real-time computation.

Article Details

How to Cite
Viet Tuan, P. ., Anh Nghiem Quan, . V. ., Ngoc Son, . P. ., Quang Nguyen, S. ., & Viet Hung, P. . (2023). Exploiting Intelligent Reflecting Surface for Wireless Power Transfer via Optimization and Deep Learning Approaches. ECTI Transactions on Electrical Engineering, Electronics, and Communications, 21(3), 251465 . https://doi.org/10.37936/ecti-eec.2023213.251465
Issue
Vol. 21 No. 3 (2023): Regular Issue (October 2023)
Section
Research Article
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