Joint Hybrid Beamforming Design for IRS-Assisted mmWave Full-Duplex MIMO Systems

This paper proposes a joint hybrid beamforming design for intelligent reflecting surface assisted (IRS-JHBF) millimeter wave (mmWave) full-duplex (FD) multiple-input multipleoutput (MIMO) systems. The proposed IRS-JHBF consists of analog beamformers, digital precoder/combiner and IRS. The analog beamformers are designed by angle-of-departure (AoD) and angle-of arrival (AoA) information of mmWave channel. Then, we employ singular value decomposition (SVD) and minimizing the mean square error (MMSE) to complete the digital precoder and combiner. Finally, the IRS phase shifts are optimized via the multivariate particle swarm optimization (MV-PSO) algorithm to maximize the system sum rate. Simulation results demonstrate that the proposed IRS-JHBF system significantly eliminates the self-interference and increases the achievable sum rate.

Authors

Institutions

Publication Details

Published
2025-06-17
DOI
https://doi.org/10.1109/vtc2025-spring65109.2025.11174640
Primary Topic
Millimeter-Wave Propagation and Modeling
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Joint Hybrid Beamforming Design for IRS-Assisted mmWave Full-Duplex MIMO Systems

Chen Wang, Yunfei Wang, Xinming Zhao, Jianing Zhao et al.
Millimeter-Wave Propagation and Modeling
article

Joint Hybrid Beamforming Design for IRS-Assisted mmWave Full-Duplex MIMO Systems

Chen Wang, Yunfei Wang, Xinming Zhao, Jianing Zhao, Panfeng Bao
article en

Abstract

This paper proposes a joint hybrid beamforming design for intelligent reflecting surface assisted (IRS-JHBF) millimeter wave (mmWave) full-duplex (FD) multiple-input multipleoutput (MIMO) systems. The proposed IRS-JHBF consists of analog beamformers, digital precoder/combiner and IRS. The analog beamformers are designed by angle-of-departure (AoD) and angle-of arrival (AoA) information of mmWave channel. Then, we employ singular value decomposition (SVD) and minimizing the mean square error (MMSE) to complete the digital precoder and combiner. Finally, the IRS phase shifts are optimized via the multivariate particle swarm optimization (MV-PSO) algorithm to maximize the system sum rate. Simulation results demonstrate that the proposed IRS-JHBF system significantly eliminates the self-interference and increases the achievable sum rate.

Southeast University (CN)
Openalex Percentile: Top 73%
Millimeter-Wave Propagation and Modeling
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.