基于有限反馈的毫米波MIMO系统的混合预编码方法

尤若楠; 潘鹏; 张丹; 王海泉

doi:10.11959/j.issn.1000−0801.2018163

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基于有限反馈的毫米波MIMO系统的混合预编码方法

研究与开发 | 更新时间：2024-06-05

- 基于有限反馈的毫米波MIMO系统的混合预编码方法
- Hybrid precoding method for mmWave MIMO systems based on limited feedback
- 电信科学 2018年34卷第8期页码：119-128
- 作者机构：
- 作者简介：
  
  [ "尤若楠（1992−），女，杭州电子科技大学通信工程学院硕士生，主要研究方向为毫米波通信。" ]
  [ "潘鹏（1983−），男，杭州电子科技大学通信工程学院副教授，主要研究方向为MIMO及大规模MIMO预编码和容量分析、毫米波通信。" ]
  [ "张丹（1993−），女，杭州电子科技大学通信工程学院硕士生，主要研究方向为毫米波通信。" ]
  [ "王海泉（1964−），男，杭州电子科技大学通信工程学院教授、博士生导师，主要研究方向为无线通信、多天线系统、信号检测、信息论等。" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(61401130)
- DOI：10.11959/j.issn.1000−0801.2018163
  中图分类号： TN928
- 网络出版日期：2018-08，
  
  纸质出版日期：2018-08-20
- 稿件说明：
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尤若楠, 潘鹏, 张丹, 等. 基于有限反馈的毫米波MIMO系统的混合预编码方法[J]. 电信科学, 2018,34(8):119-128.

Ruonan YOU, Peng PAN, Dan ZHANG, et al. Hybrid precoding method for mmWave MIMO systems based on limited feedback[J]. Telecommunications science, 2018, 34(8): 119-128.
尤若楠, 潘鹏, 张丹, 等. 基于有限反馈的毫米波MIMO系统的混合预编码方法[J]. 电信科学, 2018,34(8):119-128. DOI： 10.11959/j.issn.1000−0801.2018163.

Ruonan YOU, Peng PAN, Dan ZHANG, et al. Hybrid precoding method for mmWave MIMO systems based on limited feedback[J]. Telecommunications science, 2018, 34(8): 119-128. DOI： 10.11959/j.issn.1000−0801.2018163.

摘要

针对发送端未知信道状态信息下毫米波MIMO系统的混合预编码问题，提出了一种基于有限反馈的混合预编码算法。该算法首先将模拟及数字预编码的混合优化问题简化为模拟预编码和数字预编码独立优化问题，模拟预编码将依据该独立优化函数在所设计的模拟预编码码本内选取最佳的预编码矩阵；然后，根据已获得的模拟预编码矩阵，并基于最小二乘法获得数字预编码矩阵，在数字预编码码本内选择与其距离最近的码字作为反馈数字预编码矩阵；最后，接收机将模拟和数字预编码矩阵的索引值反馈回发射机。仿真结果显示，所提算法能够在复杂度和性能上实现较好的均衡。

Abstract

A hybrid precoding algorithm for millimeter wave (mmWave) MIMO systems without knowledge of channel state information at the transmitter was proposed based on the limited feedback.Specifically

the joint optimization problem of analog precoding and digital precoding was firstly separated into two independent optimization problems

which correspond to the analog precoding and digital precoding respectively.Based on this analog precoding codebook

the best precoding matrix was selected by analog precoding in the designed analog precoding codebook.Secondly

according to the obtained analog precoding matrix

the digital precoding matrix was obtained through the least square method

and then

the codeword closest to it in the random vector quantization codebook was selected as the feedback digital precoding matrix.Finally

the receiver feeds the index values of the analog and digital precoding matrices back to the transmitter.Simulation results show that the proposed algorithm can achieve better balance between complexity and performance.

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Keywords

references

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