基于矩阵完备的低复杂度毫米波大规模MIMO信道估计

邱佳锋

doi:10.11959/j.issn.1000-0801.2020051

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基于矩阵完备的低复杂度毫米波大规模MIMO信道估计

研究与开发 | 更新时间：2024-06-05

- 基于矩阵完备的低复杂度毫米波大规模MIMO信道估计
- Low-complexity massive MIMO channel estimation for mmWave systems via matrix completion
- 电信科学 2020年36卷第4期页码：99-106
- 作者机构：
- 作者简介：
  
  [ "邱佳锋（1995- ），男，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大规模MIMO系统信道估计" ]
- 基金信息：
  
  浙江省自然科学基金资助项目;The Natural Science Foundation of Zhejiang Province of China(LY12F01008)
- DOI：10.11959/j.issn.1000-0801.2020051
  中图分类号： TN911.22
- 网络出版日期：2020-04，
  
  纸质出版日期：2020-04-20
- 稿件说明：
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邱佳锋. 基于矩阵完备的低复杂度毫米波大规模MIMO信道估计[J]. 电信科学, 2020,36(4):99-106.

Jiafeng QIU. Low-complexity massive MIMO channel estimation for mmWave systems via matrix completion[J]. Telecommunications science, 2020, 36(4): 99-106.
邱佳锋. 基于矩阵完备的低复杂度毫米波大规模MIMO信道估计[J]. 电信科学, 2020,36(4):99-106. DOI： 10.11959/j.issn.1000-0801.2020051.

Jiafeng QIU. Low-complexity massive MIMO channel estimation for mmWave systems via matrix completion[J]. Telecommunications science, 2020, 36(4): 99-106. DOI： 10.11959/j.issn.1000-0801.2020051.

摘要

针对毫米波大规模多入多出系统为取得可靠信道估计需要高计算复杂度的缺陷，结合毫米波信道固有的低秩性提出一种低复杂度的毫米波波束域信道估计算法。该算法联合利用毫米波信道波束域稀疏性和天线域低秩性以更短训练间隔实现精确恢复。将信道估计看作矩阵完备问题，利用交替方向乘子法（ADMM）实现快速收敛，并采用快速随机奇异值阈值法将相应计算复杂度降低一个数量级。仿真结果表明，推荐算法在获得令人满意信道估计性能的同时依旧可以保持低复杂度。

Abstract

Due to the high computational complexity of mmWave massive MIMO systems realizing reliable channel estimation

a low-complexity mmWave beamspace channel estimation algorithm was proposed utilizing the inherent low-rank of the mmWave channel.The proposed algorithm jointly exploited the channel sparsity in the beamspace domain and its low-rank property in the antenna domain to provide more accurate recovery

especially for shorter training intervals.By regarding the channel estimation as matrix completion problem

the proposed algorithm was based on the alternating direction method of multipliers with fast convergence properties and exploited fast randomized singular value thresholding to significantly reduce the corresponding complexity.The simulation result shows that the proposed algorithm can achieve satisfactory channel estimation performance while maintaining low complexity.

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references

林泓池 , 孙文彬 , 郭继冲 , 等 . 5G先进技术研究进展 [J ] . 电信科学 , 2018 , 34 ( 8 ): 34 - 45 .

LIN H C , SUN W B , GUO J C , et al . Research progress of 5G advanced technologies [J ] . Telecommunication Science , 2018 , 34 ( 8 ): 34 - 45 .

申敏 , 徐浩 , 何云 , 等 . 毫米波 MIMO 系统中迭代最小均方误差混合波束成形算法 [J ] . 电信科学 , 2017 , 33 ( 8 ): 77 - 84 .

SHEN M , XU H , HE Y , et al . Alternating minimum mean square error hybrid beamforming algorithm in mmWave MIMO system [J ] . Telecommunication Science , 2017 , 33 ( 8 ): 77 - 84 .

HEATH R , GONZALEZ-PRELCIC N , ROH W , et al . An overview of signal processing techniques for millimeter wave MIMO systems [J ] . IEEE Journal of Selected Topics in Signal Processing , 2016 , 10 ( 3 ): 436 - 453 .

MENDEZ-RIAL R , RUSU C , GONZALEZ-PRELCIC N , et al . Hybrid MIMO architectures for millimeter wave communications:phase shifters or switches [J ] . IEEE Access , 2016 , 4 ( 3 ): 247 - 267 .

LI X , FANG J , LI H , et al . Millimeter wave channel estimation via exploiting joint sparse and low-rank structures [J ] . IEEE Transactions on Wireless Communications , 2018 , 17 ( 2 ): 1123 - 1133 .

VLACHOS E , ALEXANDROPOULOS G , THOMPSON J . Massive MIMO channel estimation for millimeter wave systems via matrix completion [J ] . IEEE Signal Processing Letters , 2018 , 25 ( 11 ): 1675 - 1679 .

BOYD S , PARIKH N , PELEATO E , et al . Distributed optimization and statistical learning via the alternating direction method of multipliers [J ] . Foundations and Trends in Machine Learning , 2011 , 3 ( 1 ): 1 - 122 .

CAI J , CANDES E , SHEN Z . A singular value thresholding algorithm for matrix completion [J ] . SIAM Journal on Optimization , 2010 , 20 ( 4 ): 1956 - 1982 .

MU Y , DONG J , YUAN X , et al . Accelerated low-rank visualrecovery by random projection [C ] // Proceedings of Computer Vision and Pattern Recognition . Piscataway:IEEE Press , 2011 : 2609 - 2616 .

OH T , MATSUSHITA Y , TAI Y , et al . Fast randomized singular value there sholding for low-rank optimizaition [J ] . IEEE Transactions on Pattern Analysis and Machine Intelligence , 2018 , 40 ( 2 ): 376 - 391 .

ALKHATEEB A , AYACH O , LEUS G , et al . Channel estimation an hybrid precoding for millimeter wave cellular systems [J ] . IEEE Journal of Selected Topics in Signal Processing , 2014 , 8 ( 5 ): 831 - 846 .

KIM T , LOVE D . Virtual AoA and AoD estimation for sparse millimeter wave MIMO channels [C ] // Proceedings of IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications . Piscataway:IEEE Press , 2015 : 146 - 150 .

LU J , LIANG G , SUN J , et al . A sparse interactive model for matrix completion with side information [J ] . Advances in Neural Information Processing Systems , 2016 8 ( 29 ):4071.

YEN J , WANG L . Simplifying fuzzy rule-based models using orthogonal transformation methods [J ] . IEEE Transactions on Systems,Man,and Cybernetics-part B:Cybernetics , 1999 , 29 ( 1 ): 13 - 24 .

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