Open Access

ARTICLE

Fairness-Aware Harvested Energy Efficiency Algorithm for IRS-Aided Intelligent Sensor Networks with SWIPT

Yingying Chen¹, Weiqiang Tan², Shidang Li^3,*

1 School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou, 221116, China
2 School of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou, 510006, China
3 School of Physics and Electronic Engineering, Jiangsu Normal University, Xuzhou, 221116, China

* Corresponding Author: Shidang Li. Email:

(This article belongs to the Special Issue: Recent Advances in Backscatter and Intelligent Reflecting Surface Communications for 6G-enabled Internet of Things Networks)

Computer Modeling in Engineering & Sciences 2023, 137(3), 2675-2691. https://doi.org/10.32604/cmes.2023.028533

Received 23 December 2022; Accepted 14 March 2023; Issue published 03 August 2023

Abstract

In this paper, a novel fairness-aware harvested energy efficiency-based green transmission scheme for wireless information and power transfer (SWIPT) aided sensor networks is developed for active beamforming of multiantenna transmitter and passive beamforming at intelligent reflecting surfaces (IRS). By optimizing the active beamformer assignment at the transmitter in conjunction with the passive beamformer assignment at the IRS, we aim to maximize the minimum harvested energy efficiency among all the energy receivers (ER) where information receivers (IR) are bound to the signal-interference-noise-ratio (SINR) and the maximum transmitted power of the transmitter. To handle the non-convex problem, both semi-definite relaxation (SDR) and block coordinate descent technologies are exploited. Then, the original problem is transformed into two convex sub-problems which can be solved via semidefinite programming. Numerical simulation results demonstrate that the IRS and energy beamformer settings in this paper provide greater system gain than the traditional experimental setting, thereby improving the fairness-aware harvested energy efficiency of the ER.

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Keywords

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