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Reflection Resource Management for Intelligent Reflecting Surface Aided Wireless Networks by Yulan Gao; Chao Yong; Zehui Xiong; Jun Zhao; Yue Xiao; Dusit Niyato is a Engineering article available to read on EtoBox.

What is Reflection Resource Management for Intelligent Reflecting Surface Aided Wireless Networks about?

In this paper, the adoption of an intelligent reflecting surface (IRS) for multiple user pairs in two-hop networks is investigated. Different from the existing studies on IRS that mainly focused on tuning the reflection coefficients of all elements, we consider the implementation of true reflection resource management (RRM) through the identification of the best triggered module subset. More precisely, the implementation of true RRM builds on the premise of our proposed modular IRS structure consisting of multiple independent and controllable modules. In the context of modular IRS structure, we investigate the signalto-interference-plus-noise ratio (SINR)-based max-min problem subject to per source terminals (STs) power budgets and module size constraint, via joint triggered module subset identification, transmit power allocation, and the corresponding passive beamforming. Whereas this problem is NP-hard due to the module size constraint, which can be addressed by the convex sparsityinducing approximation to the hard module size constraint using mixed 1,F -norm, where it yields a suitable semidefinite relaxation. Using techniques from separable convex programming, we provide a two-

Who reads Reflection Resource Management for Intelligent Reflecting Surface Aided Wireless Networks?

Author

Yulan Gao; Chao Yong; Zehui Xiong; Jun Zhao; Yue Xiao; Dusit Niyato

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Published

2021

Language

EN

Field

Engineering (Physical Sciences)