A Robust Fairness Resource Allocation Algorithm for SWIPT-Enabled Internet of Things with IRS

被引：0
作者：
Li S. [1 ]
Chen J. [1 ]
Chen Y. [2 ]
Long C. [1 ]
Xu J. [3 ]
Li C. [4 ]
机构：
[1] School of Physics and Electronic Engineering, Jiangsu Normal University, Xuzhou
[2] School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou
[3] Sino-Russian Institute, Jiangsu Normal University, Xuzhou
[4] State Key Laboratory of Mobile Communication, Southeast University, Nanjing
来源：
Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology | 2024年 / 46卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Intelligent Reflecting Surface (IRS); Maximizing fairness energy; Robust optimization algorithm; Simultaneous Wireless Information and Power Transfer (SWIPT);
D O I：
10.11999/JEIT221509
中图分类号：
学科分类号：
摘要：
Focusing on examine the influence of channel errors and the fairness of energy collected by users in 6G internet of things, the problem of maximizing fairness energy for Intelligent Reflecting Surface (IRS)-aided Simultaneous Wireless Information and Power Transfer (SWIPT) is examined when the users have a limited signal-to-interference noise ratio, a transmission power constraint and a reflection phase mode one constraint. As part of the process of solving the nonconvex problem, Schur Complete and S-Process are used to convert the infinite dimensional constraint into a linear inequality involving a finite dimensional matrix, and then the original difficult-to-solve problem is transformed into a standard convex optimization problem using the penalty function and continuous convex approximation, and then an iterative robust fairness energy acquisition algorithm is proposed. Numerical results indicate that the proposed robust optimization algorithm improves the fairness of network harvested energy significantly compared to previous algorithms. © 2024 Journal of Pattern Recognition and Artificial Intelligence. All rights reserved.
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页码：129 / 137
页数：8
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