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首页> 外文期刊>Wireless Communications Letters, IEEE >Wideband mmWave Channel Estimation for Hybrid Massive MIMO With Low-Precision ADCs
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Wideband mmWave Channel Estimation for Hybrid Massive MIMO With Low-Precision ADCs

机译:具有低精度ADC的混合大规模MIMO的宽带毫米波信道估计

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摘要

In this letter, we investigate channel estimation for wideband millimeter-wave (mmWave) massive multiple-input multiple-output under hybrid architecture with low-precision analog-to-digital converters (ADCs). To design channel estimation for the hybrid structure, both analog processing components and frequency-selective digital combiners need to be optimized. The proposed channel estimator follows the typical linear-minimum-mean-square-error structure and applies for an arbitrary channel model. Moreover, for sparsity channels as in mmWave, the proposed estimator performs more efficiently by incorporating orthogonal matching pursuit to mitigate quantization noise caused by low-precision ADCs. Consequently, the proposed estimator outperforms conventional ones as demonstrated by computer simulation results.
机译:在这封信中,我们研究了在具有低精度模数转换器(ADC)的混合架构下,宽带毫米波(mmWave)大规模多输入多输出的信道估计。为了设计混合结构的信道估计,需要同时优化模拟处理组件和频率选择性数字组合器。拟议的信道估计器遵循典型的线性最小均方误差结构,并适用于任意信道模型。此外,对于毫米波中的稀疏信道,所提出的估计器通过合并正交匹配追踪以减轻由低精度ADC引起的量化噪声,可以更有效地执行。因此,如计算机仿真结果所示,拟议的估算器优于传统估算器。

著录项

  • 来源
    《Wireless Communications Letters, IEEE》 |2019年第1期|285-288|共4页
  • 作者单位

    Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Jiangsu, Peoples R China|Xidian Univ, State Key Lab Integrated Serv Networks, Xian 710071, Shaanxi, Peoples R China;

    Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Jiangsu, Peoples R China|Xidian Univ, State Key Lab Integrated Serv Networks, Xian 710071, Shaanxi, Peoples R China;

    Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Jiangsu, Peoples R China;

    Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Jiangsu, Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    MmWave; channel estimation; hybrid; ADC;

    机译:毫米波信道估计混合ADC;

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