Base Station Beamforming Design in Near-field XL-IRS Beam Training

Wang，Tao1; You，Changsheng2; Zhou，Fasheng3; Yin，Changchuan1

2024

10.1109/LCOMM.2024.3360266

IEEE Communications Letters   影响因子和分区

1089-7798

1558-2558

Existing research on extremely large-scale intelligent reflecting surface (XL-IRS) beam training has widely assumed the far-field channel model for the base station (BS)-IRS link. However, this approach may cause degraded beam training performance in practice due to the near-field channel model of the BS-IRS link. To address this issue, we propose two efficient schemes to optimize BS beamforming for improving the XL-IRS beam training performance. Specifically, the first scheme aims to maximize total received signal power on the XL-IRS, which generalizes the existing angle based BS beamforming design and can be resolved using the singular value decomposition (SVD) method. The second scheme aims to maximize the ℓ₁-norm of incident signals on the XL-IRS, which is shown to achieve the maximum received power at the user. To solve the non-convex ℓ₁-norm maximization problem, we propose an efficient algorithm by using the alternating optimization (AO) technique. Numerical results show that the proposed AO based BS beamforming design outperforms the SVD/angle based BS beamforming in terms of success rate and achievable data rate.

Aperture antennas Array signal processing base station beamforming Base stations Channel estimation Channel models Extremely large-scale intelligent reflecting surface (XL-IRS) near-field communication Signal to noise ratio Training XL-IRS beam training

SCI ; EI

英语

其他

COMPUTER SCIENCE

2-s2.0-85184333488

Scopus

1.Beijing Laboratory of Advanced Information Networks, Beijing University of Posts and Telecommunications (BUPT), Beijing, China
2.Department of Electrical and Electronic Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, China
3.School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, China

Wang，Tao,You，Changsheng,Zhou，Fasheng,et al. Base Station Beamforming Design in Near-field XL-IRS Beam Training[J]. IEEE Communications Letters,2024,PP(99):1-1.

Wang，Tao,You，Changsheng,Zhou，Fasheng,&Yin，Changchuan.(2024).Base Station Beamforming Design in Near-field XL-IRS Beam Training.IEEE Communications Letters,PP(99),1-1.

Wang，Tao,et al."Base Station Beamforming Design in Near-field XL-IRS Beam Training".IEEE Communications Letters PP.99(2024):1-1.