English

Fast Near-Field Beam Training for Extremely Large-Scale Array

Information Theory 2022-09-30 v1 Signal Processing math.IT

Abstract

In this letter, we study efficient near-field beam training design for the extremely large-scale array (XL-array) communication systems. Compared with the conventional far-field beam training method that searches for the best beam direction only, the near-field beam training is more challenging since it requires a beam search over both the angular and distance domains due to the spherical wavefront propagation model. To reduce the near-field beam-training overhead based on the two-dimensional exhaustive search, we propose in this letter a new two-phase beam training method that decomposes the two-dimensional search into two sequential phases. Specifically, in the first phase, the candidate angles of the user is determined by a new method based on the conventional far-field codebook and angle-domain beam sweeping. Then, a customized polar-domain codebook is employed in the second phase to find the best effective distance of the user given the shortlisted candidate angles. Numerical results show that our proposed two-phase beam training method significantly reduces the training overhead of the exhaustive search and yet achieves comparable beamforming performance for data transmission.

Keywords

Cite

@article{arxiv.2209.14798,
  title  = {Fast Near-Field Beam Training for Extremely Large-Scale Array},
  author = {Yunpu Zhang and Xun Wu and Changsheng You},
  journal= {arXiv preprint arXiv:2209.14798},
  year   = {2022}
}

Comments

We proposed a novel two-phase near-field beam training method for the XL-array communication systems. The paper has been accepted by IEEE Wireless Communications Letters

R2 v1 2026-06-28T02:22:33.521Z