Beam Switching with Low Control Overhead for Millimeter-wave Communication

Ashim Kumar, Arghyadip Roy, R. Bhattacharjee
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Abstract

Mm-wave communication using massive Multiple-Input Multiple Output (MIMO) is highly directional in nature, hence making beam scanning and alignment a crucial aspect. In high mobility scenarios, frequent beam scanning may incur a performance degradation due to high control overhead. In this paper, we have adopted a supervised learning approach to determine the precoders and combiners for a hybrid beamforming architecture. To avoid frequent beam scanning and switching, we propose an overhead-aware strategy that addresses a trade-off between the spectral efficiency (SE) and the overhead signalling. Simulations are performed using channel data generated using the open source channel simulator NYUSIM.
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毫米波通信中低控制开销的波束交换
使用大量多输入多输出(MIMO)的毫米波通信本质上是高度定向的,因此波束扫描和对准是一个至关重要的方面。在高迁移率情况下,由于高控制开销,频繁的波束扫描可能导致性能下降。在本文中,我们采用了一种监督学习方法来确定混合波束形成架构的预编码器和组合器。为了避免频繁的波束扫描和切换,我们提出了一种开销感知策略,该策略解决了频谱效率(SE)和开销信令之间的权衡。使用使用开源信道模拟器NYUSIM生成的信道数据进行仿真。
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