Adaptive initial beam search for sparse millimeter wave channels

M. Jasim, N. Ghani
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引用次数: 10

Abstract

Narrow beamforming solutions for millimeter wave cellular networks require mobile and base stations to exhaustively search all angular space. This scanning is mandatory in order to detect the unique optimum beamforming and combining vectors prior to control and data signaling. However exhaustive search yields large computational complexity and increases beam discovery time and control plane latency. Hence this paper presents some novel adaptive search algorithms to accelerate initial beam acquisition in sparse millimeter wave channels in non-line of sight environments. Namely the beam search is formulated as an optimization problem, and fast search procedures are presented based upon Luus Jaakola, divide and conquer, and Tabu direct pattern methods. The proposed algorithms deliver significant performance improvements versus existing beam search solutions, i.e., 25–99%.
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稀疏毫米波信道的自适应初始波束搜索
毫米波蜂窝网络的窄波束形成解决方案要求移动和基站彻底搜索所有角度空间。这种扫描是强制性的,以便在控制和数据信号之前检测到独特的最佳波束形成和组合矢量。然而,穷举搜索产生了巨大的计算复杂度,增加了波束发现时间和控制面延迟。为此,本文提出了一些新的自适应搜索算法来加速非视线环境下稀疏毫米波信道的初始波束捕获。即将光束搜索表述为优化问题,提出了基于Luus Jaakola法、分治法和Tabu直接模式法的快速搜索方法。与现有的波束搜索解决方案相比,所提出的算法提供了显着的性能改进,即25-99%。
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