eprintid: 10164842
rev_number: 7
eprint_status: archive
userid: 699
dir: disk0/10/16/48/42
datestamp: 2023-02-14 09:30:13
lastmod: 2023-02-14 09:30:13
status_changed: 2023-02-14 09:30:13
type: proceedings_section
metadata_visibility: show
sword_depositor: 699
creators_name: Zhang, S
creators_name: Yang, Z
creators_name: Chen, M
creators_name: Liu, D
creators_name: Wong, KK
creators_name: Poor, HV
title: Performance Optimization for Intelligent Reflecting Surface Assisted Multicast MIMO Networks
ispublished: pub
divisions: UCL
divisions: B04
divisions: C05
divisions: F46
keywords: Manifolds,
Multicast algorithms,
Array signal processing,
Surface waves,
Simulation,
Performance gain,
Matrices
note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
abstract: In this paper, the problem of maximizing the sum rate of all users in an intelligent reflecting surface (IRS)-assisted millimeter wave multicast multiple-input multiple-output communication system is studied. In the considered model, one IRS is deployed to assist the communication from a multi-antenna base station (BS) to the multi-antenna users that are clustered into several groups. Our goal is to maximize the sum rate of all users by jointly optimizing the transmit beamforming matrices of the BS, the receive beamforming matrices of the users, and the phase shifts of the IRS. To solve this non-convex problem, we first use a block diagonalization method to represent the beamforming matrices of the BS and the users by the phase shifts of the IRS. Then, substituting the expressions of the beamforming matrices of the BS and the users, the original sum-rate maximization problem can be transformed into a problem that only needs to optimize the phase shifts of the IRS. To solve the transformed problem, a manifold method is used. Simulation results show that the proposed scheme can achieve up to 13.3 % gain in terms of the sum rate of all users compared to the algorithm that optimizes the hybrid beamforming matrices of the BS and the users using our proposed scheme and randomly determines the phase shifts of the IRS.
date: 2022-01-01
date_type: published
publisher: IEEE
official_url: https://doi.org/10.1109/GLOBECOM48099.2022.10000992
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 2004805
doi: 10.1109/GLOBECOM48099.2022.10000992
isbn_13: 9781665435406
lyricists_name: Wong, Kai-Kit
lyricists_id: KWONG98
actors_name: Wong, Kai-Kit
actors_id: KWONG98
actors_role: owner
full_text_status: public
pres_type: paper
publication: 2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings
place_of_pub: Rio de Janeiro, Brazil
pagerange: 5838-5843
event_title: GLOBECOM 2022 - 2022 IEEE Global Communications Conference
event_dates: 4 Dec 2022 - 8 Dec 2022
book_title: 2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings
citation:        Zhang, S;    Yang, Z;    Chen, M;    Liu, D;    Wong, KK;    Poor, HV;      (2022)    Performance Optimization for Intelligent Reflecting Surface Assisted Multicast MIMO Networks.                     In:  2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings.  (pp. pp. 5838-5843).  IEEE: Rio de Janeiro, Brazil.       Green open access   
 
document_url: https://discovery-pp.ucl.ac.uk/id/eprint/10164842/1/a973-zhang%20paper.pdf