| 摘要: |
| 信道估计是大规模多输入多输出（Multiple-Input Multiple-Output,MIMO）毫米波（Millimeter Wave,mmWave）系统关键技术之一。梳理了近几年大规模MIMO毫米波的信道估计策略，重点从压缩感知（Compressive Sensing,CS）、参数估计和深度学习三个方面进行了描述与分析。通过算法性能的对比，总结了毫米波信道估计目前存在的问题以及未来发展的趋势。 |
| 关键词: 大规模MIMO 毫米波通信 信道估计 压缩感知 参数估计 深度学习 |
| DOI： |
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| 基金项目:国家自然科学基金资助项目(61702066)；重庆市自然科学基金项目(cstc2019jcyj-msxmX0681)；重庆市教委科学技术重点研究项目(KJZD-M201900601) |
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| Channel Estimation for 5G mmWave Communications Systems:a Survey |
| LUO Hao,YU Xiulan,ZHANG Zufan,GAN Chenquan |
| (School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China) |
| Abstract: |
| Channel estimation is one of the key techniques of massive multiple-input multiple-output(MIMO) millimeter wave(mmWave) systems.The channel estimation strategies of massive MIMO mmWave in recent years are combed,focus with on the description and analysis from the three aspects of compressed sensing,parameter estimation,and deep learning.Through performance comparisons of algorithms,the current problems and the future development trends of mmWave channel estimation are summarized. |
| Key words: massive MIMO mmWave communication channel estimation compressed sensing parameter estimation deep learning |
