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arXiv · 2209.14798

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

Yunpu Zhang·Xun Wu·Changsheng You
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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.

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Yunpu Zhang, Xun Wu, Changsheng You. 2022-09-29. Fast Near-Field Beam Training for Extremely Large-Scale Array. https://arxiv.org/abs/2209.14798

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