论文标题

部分可观测时空混沌系统的无模型预测

Near-Field Rainbow: Wideband Beam Training for XL-MIMO

论文作者

Cui, Mingyao, Dai, Linglong, Wang, Zhaocheng, Zhou, Shidong, Ge, Ning

论文摘要

宽带非常大规模的多输入 - 元素输出(XL-MIMO)是一种有前途的技术,可以通过波束成形和空间多路复用来实现未来6G系统中的TBPS数据速率。由于宽带XL-MIMO的带宽和大量天线,将诱发显着的近场横梁拆分效果,其中不同频率下的光束集中在不同的位置上。近场梁拆分效应导致严重的阵列增益损失,因此现有的作品主要集中在使用时延迟(TD)束形方面来补偿此损失。相比之下,本文表明,尽管近场束拆分效果降低了阵列的增长,但它也提供了一种新的可能性,可以实现快速的近场梁训练。具体而言,我们首先揭示了近场可控光束拆分效果的机制。该效果表明,通过专门设计延迟参数,TD束式器能够控制近场束拆分效果的程度,即不同频率的光束可以灵活地占据所需的位置范围。由于与棱镜引起的自然光的分散相似,因此本文中也称之为近场彩虹。然后,利用近场彩虹效应,提出了快速宽带梁训练方案。在我们的方案中,光束形成矢量的近距离形式被精心得出,以使不同频率的光束专注于不同所需的位置。通过这种方式,可以通过仅通过一个无线电频率(RF)链同时生成多个光束来迅速搜索具有最大阵列增益的最佳光束成形向量。最后,仿真结果表明,该方案能够通过非常低的训练开销实现近乎最佳的近场梁训练。

Wideband extremely large-scale multiple-input-multiple-output (XL-MIMO) is a promising technique to achieve Tbps data rates in future 6G systems through beamforming and spatial multiplexing. Due to the extensive bandwidth and the huge number of antennas for wideband XL-MIMO, a significant near-field beam split effect will be induced, where beams at different frequencies are focused on different locations. The near-field beam split effect results in a severe array gain loss, so existing works mainly focus on compensating for this loss by utilizing the time delay (TD) beamformer. By contrast, this paper demonstrates that although the near-field beam split effect degrades the array gain, it also provides a new possibility to realize fast near-field beam training. Specifically, we first reveal the mechanism of the near-field controllable beam split effect. This effect indicates that, by dedicatedly designing the delay parameters, a TD beamformer is able to 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, this effect is also termed as the near-field rainbow in this paper. Then, taking advantage of the near-field rainbow effect, a fast wideband beam training scheme is proposed. In our scheme, the close form of the beamforming vector is elaborately derived to enable beams at different frequencies to be focused on different desired locations. By this means, the optimal beamforming vector with the largest array gain can be rapidly searched out by generating multiple beams focused on multiple locations simultaneously through only one radio-frequency (RF) chain. Finally, simulation results demonstrate the proposed scheme is able to realize near-optimal nearfield beam training with a very low training overhead.

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