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Anti-Blockage Beam Training for Massive MIMO Millimeter Wave Systems

机译:大规模MIMO毫米波系统的防阻塞波束训练

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Due to the short wavelength of millimeter wave (mmWave) and high directional beamforming, the 60GHz massive MIMO systems are highly vulnerable to link blockage. Beam switching to unblocked direction is an effective solution to overcome blockage. To this end, a set of backup beam pairs for beam switching must be identified at initial beam training. In this work, a low complexity beam training scheme with support for backup beam identification is proposed. Considering sparsity and clustered characteristics of mmWave channels and high probability for adjacent beams to be simultaneously blocked, we propose a new criterion for the selection of backup beams based on peak beam grouping, and design two beam grouping algorithms. The detailed procedure for beam switching when a blockage occurs is also given. Simulation results show that the proposed beam training scheme achieves near-optimal performance at initial beam training stage. Furthermore, the new method for identifying backup beam pairs is more effective to improve the spectral efficiencies of systems under blockage environments.
机译:由于毫米波(mmWave)的短波长和高定向波束形成,60GHz大规模MIMO系统极易受到链路阻塞的影响。光束切换到无遮挡方向是克服遮挡的有效解决方案。为此,必须在初始波束训练时识别一组用于波束切换的备用波束对。在这项工作中,提出了一种支持后备波束识别的低复杂度波束训练方案。考虑到毫米波通道的稀疏性和聚类特性以及相邻光束被同时遮挡的高概率,我们提出了一种基于峰值光束分组的备用光束选择准则,并设计了两种光束分组算法。还给出了发生阻塞时光束切换的详细过程。仿真结果表明,所提出的波束训练方案在初始波束训练阶段达到了近乎最优的性能。此外,用于识别备用光束对的新方法更有效地提高了在阻塞环境下系统的光谱效率。

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