Abstract:

The eXtremely Large-scale Multiple-Input-Multiple-Output （XL-MIMO） system can significantly improve channel capacity. However， traditional Uniform Linear Arrays （ULAs） experience a drastic reduction in the near-field region at large incident and emitted angles， leading to limited signal coverage. The use of Uniform Circular Arrays （UCAs） can effectively expand the near-field regions， but renders low-overhead beam training schemes based on ULA impractical. To reduce the overhead of near-field beam training with UCA， a new fast beam training scheme was proposed. In the first stage， UCA was approximated as ULA， and a joint method was used to construct a far-field hierarchical codebook for angle domain user search； in the second stage， based on the angles obtained from the first stage， UCA was used for exhaustive search in both angle and distance domains. Simulation results on a UCA system with 512 antennas indicate that the proposed scheme requires only 28 training overheads， while maintaining good robustness across different Signal-to-Noise Ratio （SNR） conditions， and its rate performance achieves 99.16% of the benchmark.

Key words: eXtremely Large-scale Multiple-Input Multiple-Output (XL-MIMO), Uniform Circular Array (UCA), near field, beam training, hierarchical codebook

摘要：

超大规模多输入多输出（XL-MIMO）系统能显著提高信道容量。然而，传统的均匀线性阵列（ULA）在大入射角/出射角下，近场区域会急剧缩小，导致信号覆盖受限。使用均匀圆形阵列（UCA）可以有效扩大近场区域，但这也使得基于ULA的低开销波束训练方案不再适用。为了减少UCA近场波束训练的开销，提出一种新的快速波束训练方案：在第一阶段将UCA近似为ULA，使用ULA联合的方式构建远场分层码本进行角度域的用户搜索；在第二阶段，基于第一阶段搜索得到的角度，使用UCA进行角度与距离的穷举搜索。仿真结果表明，在天线数为512的UCA系统中，该方案仅需28个训练开销，并且在不同信噪比（SNR）条件下具有较好的鲁棒性，平均速率性能达到速率基准的99.16%。

关键词: 超大规模多输入多输出, 均匀圆形阵列, 近场, 波束训练, 分层码本