Deep Learning Based Hybrid Precoding for RIS-aided Broadband Terahertz Communication Systems in the Face of Beam Squint

Qijiang Yuan; Lixia Xiao; Chunlin He; Pei Xiao; Tao Jiang

doi:10.1109/LWC.2023.3327769

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Deep Learning Based Hybrid Precoding for RIS-aided Broadband Terahertz Communication Systems in the Face of Beam Squint

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Deep Learning Based Hybrid Precoding for RIS-aided Broadband Terahertz Communication Systems in the Face of Beam Squint

Qijiang Yuan, Lixia Xiao, Chunlin He, Pei Xiao and Tao Jiang

IEEE Wireless Communications Letters, Vol.13(2), pp.303-307

01/02/2024

DOI: https://doi.org/10.1109/LWC.2023.3327769

Abstract

Terahertz (THz)

reconfigurable intelligent surface (RIS)

hybrid precoding

deep learning

beam squint

In this letter, we design a wideband hybrid re-configurable intelligent surface network (WHRIS-Net) based on deep learning for reconfigurable intelligent surface (RIS)-assisted terahertz massive multiple-input multiple-output systems with beam squint. Firstly, the mean channel covariance matrices (MCCMs) from the base station to the RIS and from the RIS to the user are used as the inputs of WHRIS-Net. Then, a Phase-Net is applied to calculate the frequency-independent analog precoder and the phases of RIS elements. Finally, a Digital-Net designs the frequency-dependent digital precoder utilizing the MCCMs and the outputs of Phase-Net. Numerical simulations validate the effectiveness of the WHRIS-Net in terms of the sum rate and demonstrate its promising performance gain despite reduced average running time and feedback overhead. Index Terms—Terahertz (THz), reconfigurable intelligent surface (RIS), hybrid precoding, deep learning, beam squint.

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Title: Deep Learning Based Hybrid Precoding for RIS-aided Broadband Terahertz Communication Systems in the Face of Beam Squint
Creators: Qijiang Yuan (Author) - Huazhong University of Science and Technology
Lixia Xiao (Author) - Huazhong University of Science and Technology
Chunlin He (Author) - China West Normal University
Pei Xiao (Author) - University of Surrey, School of Computer Science and Electronic Engineering
Tao Jiang (Author) - University of Surrey, School of Computer Science and Electronic Engineering
Publication Details: IEEE Wireless Communications Letters, Vol.13(2), pp.303-307
Publisher: Institute of Electrical and Electronics Engineers (IEEE); PISCATAWAY
Number of pages: 5
First online publication date: 30/10/2023
Publication Date: 01/02/2024
Date accepted for publication: 22/10/2023
Grant note: This work was supported in part by the National Key Research and Development Program of China under Grant 2019YFB1803400.
Identifiers: 99821858102346; WOS:001167560000015
Copyright: © 2023 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
Academic Unit: School of Computer Science and Electronic Engineering
Language: English
Resource Type: Journal article

Deep Learning Based Hybrid Precoding for RIS-aided Broadband Terahertz Communication Systems in the Face of Beam Squint

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