Joint Phase-Noise and Channel Estimation in mmWave Massive MIMO Systems With Hybrid Structures Using Nested Tensor Decomposition

被引:0
|
作者
Zheng, Kang [1 ,2 ]
Gu, Zhihao [1 ]
Xia, Xinjiang [3 ]
Zhang, Zhaotao [4 ]
Wang, Dongming [1 ,3 ]
Zhu, Pengcheng [1 ,3 ]
机构
[1] Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R China
[2] China Mobile Zijin Innovat Inst, Nanjing 211899, Peoples R China
[3] Purple Mt Labs, Nanjing 21111, Peoples R China
[4] Nanjing R&D Ctr Broadband Wireless Commun, Nanjing 211111, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Radio frequency; Millimeter wave communication; Tensors; Channel estimation; Matrix decomposition; Estimation; Mobile communication; Hybrid structure; mmWave massive MIMO; nested-tensor decomposition; phase noise; channel estimation; OFDM; UNIQUENESS;
D O I
10.1109/TVT.2024.3446847
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper focuses on the phase-noise (PN) and channel estimation for mmWave massive MIMO systems with hybrid analog-digital structures. By considering the PN caused by the impairment of radio frequency (RF) chains, we construct the training signal as a nested CANDECOMP/PARAFAC (CP) model. After separating PN and compressed channel (inner tensor) through CP decomposition (CPD) of outer tensor, we further explore the Vandermonde structure of the factor matrix in inner tensor and propose Tensor-Train-Vandermonde-Structure-CPD (TTVSCPD) to estimate mmWave channel parameters. The simulation results verify that the accuracy and robustness of proposed algorithm are superior to traditional methods.
引用
收藏
页码:19890 / 19895
页数:6
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