Resource Management for Intelligent Reflecting Surface Assisted THz-MIMO Network

Conference paper

Ren, L., Zhang, H., Zhu, Y. and Long, K. (2021). Resource Management for Intelligent Reflecting Surface Assisted THz-MIMO Network. 2021 IEEE Global Communications Conference (GLOBECOM). Madrid, Spain 07 - 11 Dec 2021 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/globecom46510.2021.9685295
AuthorsRen, L., Zhang, H., Zhu, Y. and Long, K.
TypeConference paper
Abstract

As the preferred frequency band for future high frequency communication, the terahertz (THz) band has at-tracted wide attention. In this paper, an energy efficient resource optimization problem in THz band is studied. The massive Multiple-Input Multiple-Output (MIMO) technology and intelligent reflecting surface (IRS) are adopted to improve the capacity and energy efficiency (EE) of proposed network. An IRS assisted THz-MIMO downlink wireless network system is established. The original EE problem is decomposed into phase-shift matrix optimization and power allocation. On this basis, a distributed EE optimization algorithm is designed, which transforms the original nonlinear problem into a convex optimization problem. The simulation results reveal that the proposed distributed optimization method converges rapidly and abtains the maximum EE. This also proves that it is feasible and effective to apply both the IRS and the massive MIMO technology into THz communication network.

Year2021
Journal2021 IEEE Global Communications Conference (GLOBECOM)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Journal citationp. 21703246
Digital Object Identifier (DOI)https://doi.org/10.1109/globecom46510.2021.9685295
Accepted author manuscript
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File Access Level
Open
Publication dates
Print02 Feb 2022
Publication process dates
Deposited20 Sep 2022
Funder/ClientNational Natural Science Foundation of China
Additional information

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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