Optimality of the Discrete Fourier Transform for Beamspace Massive MU-MIMO Communication
Optimality of the Discrete Fourier Transform for Beamspace Massive MU-MIMO Communication
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DOI：
10.1109/isit45174.2021.9518255
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发表时间：
2021-07
期刊：
影响因子：
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通讯作者：
Sueda Taner;Christoph Studer
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文献类型：
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作者：
Sueda Taner;Christoph Studer
波束空间处理是一种新兴技术，可降低在毫米波 (mmWave) 和太赫兹频率下运行的大规模多用户 (MU) 多输入多输出 (MIMO) 通信系统中的基带复杂性。如此高频率下波传播的高方向性确保了用户设备和基站（BS）之间仅存在少量传输路径。为了解决波传播的稀疏性质，波束空间处理传统上会在 BS 的均匀线性天线阵列上计算空间离散傅立叶变换 (DFT)，其中每个 DFT 输出都与特定波束相关联。在本文中，我们研究了具有理想毫米波信道模型和现实信道的基于稀疏性的波束空间处理的 DFT 的最优条件。为此，我们提出了两种使用基于 $\ell^{4}$-范数的稀疏性度量来学习酉波束空间变换的算法，并从理论上和通过模拟研究了它们的最优性。
Beamspace processing is an emerging technique to reduce baseband complexity in massive multiuser (MU) multiple-input multiple-output (MIMO) communication systems operating at millimeter-wave (mmWave) and terahertz frequencies. The high directionality of wave propagation at such high frequencies ensures that only a small number of transmission paths exist between user equipments and basestation (BS). In order to resolve the sparse nature of wave propagation, beamspace processing traditionally computes a spatial discrete Fourier transform (DFT) across a uniform linear antenna array at the BS where each DFT output is associated with a specific beam. In this paper, we study optimality conditions of the DFT for sparsity-based beamspace processing with idealistic mmWave channel models and realistic channels. To this end, we propose two algorithms that learn unitary beamspace transforms using an $\ell^{4}$-norm-based sparsity measure, and we investigate their optimality theoretically and via simulations.