论文标题
快速的近场梁训练，用于极度大规模阵列
Fast Near-Field Beam Training for Extremely Large-Scale Array
论文作者
论文摘要
在这封信中，我们研究了极大的大规模阵列（XL-Array）通信系统的高效近场训练设计。与仅搜索最佳光束方向的常规远场梁训练方法相比，近场梁训练更具挑战性，因为它需要在球形波前传播模型引起的角和距离域上进行光束搜索。为了根据二维详尽的搜索减少近场束训练的开销，我们在这封信中提出了一种新的两相光束训练方法，将二维搜索分解为两个顺序阶段。具体而言，在第一阶段，用户的候选角度是由基于常规远场代码簿和角域横梁的新方法确定的。然后，在第二阶段使用定制的极性域代码簿，以找到候选人候选角度的最佳有效距离。数值结果表明，我们提出的两相梁训练方法大大降低了详尽搜索的训练开销，但在数据传输方面达到了可比的光束形成性能。
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.
