论文标题

部分可观测时空混沌系统的无模型预测

Hierarchical-Absolute Reciprocity Calibration for Millimeter-wave Hybrid Beamforming Systems

论文作者

Chen, Li, Nie, Rongjiang, Chen, Yunfei, Wang, Weidong

论文摘要

在时间划分的双链(TDD)毫米波(MMWave)中,大量多输入多输出(MIMO)系统,互惠不匹配严重降低了混合束缚(HBF)的性能。在这项工作中,为了减轻相互不匹配的不利影响,我们研究了具有完全连接的相位变速器网络的MMWave-HBF系统的互惠校准。为了降低互惠校准的开销和计算复杂性,我们首先将数字射频(RF)链和模拟RF链与波束成形设计解脱。然后,HBF系统的整个校准问题等效地分解为对应于数字链校准和模拟链校准的两个子问题。为了有效地解决校准问题,得出了针对数字链校准问题的封闭式解决方案,而对模拟链校准问题提出了迭代式接近式优化算法。为了衡量所提出的算法的性能,我们在估计不匹配系数的误差上得出了Cramér-rao下限。结果表明,数字和模拟链的不匹配系数的估计误差是不相关的,并且可以完美估计接收数字链的不匹配系数。提出了仿真结果以验证分析结果并显示提出的校准方法的性能。

In time-division duplexing (TDD) millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems, the reciprocity mismatch severely degrades the performance of the hybrid beamforming (HBF). In this work, to mitigate the detrimental effect of the reciprocity mismatch, we investigate reciprocity calibration for the mmWave-HBF system with a fully-connected phase shifter network. To reduce the overhead and computational complexity of reciprocity calibration, we first decouple digital radio frequency (RF) chains and analog RF chains with beamforming design. Then, the entire calibration problem of the HBF system is equivalently decomposed into two subproblems corresponding to the digital-chain calibration and analog-chain calibration. To solve the calibration problems efficiently, a closed-form solution to the digital-chain calibration problem is derived, while an iterative-alternating optimization algorithm for the analog-chain calibration problem is proposed. To measure the performance of the proposed algorithm, we derive the Cramér-Rao lower bound on the errors in estimating mismatch coefficients. The results reveal that the estimation errors of mismatch coefficients of digital and analog chains are uncorrelated, and that the mismatch coefficients of receive digital chains can be estimated perfectly. Simulation results are presented to validate the analytical results and to show the performance of the proposed calibration approach.

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