Near-Field Rainbow: Wideband Beam Training for XL-MIMO
Mingyao Cui, Linglong Dai, Zhaocheng Wang, Shidong Zhou, Ning Ge
Abstract
Wideband extremely large-scale multiple-input-multiple-output (XL-MIMO) plays an important role in boosting the data rate for 6G networks. Because of the huge bandwidth and the large number of antennas, wideband XL-MIMO introduces a significant near-field beam split effect, where beams at different frequencies are focused on different locations. This effect results in a severe array gain loss, and existing works mainly consider to compensate for this loss by utilizing time-delay (TD) beamforming. This paper demonstrates that despite degrading the array gain, the near-field beam split effect can also contribute to the fast near-field beam training. Specifically, we first reveal the controllable near-field beam split effect. This effect indicates that TD beamforming can control the degree of the near-field beam split effect, i.e., beams at different frequencies can flexibly occupy the desired location range. Due to the similarity with the dispersion of natural light caused by a prism, we also call this effect as “near-field rainbow”. Then, by taking advantage of the near-field rainbow, a fast wideband beam training scheme is proposed to generate beams focusing on multiple locations at multiple frequencies with the help of TD beamforming. Finally, simulation results demonstrate that the proposed scheme is able to realize efficient near-field beam training with low training overheads.