Hybrid Message Passing Channel Estimation Algorithm for Massive MIMO-OFDM Systems

被引:2
|
作者
Song, Yi [1 ]
Zhang, Chuanzong [2 ]
Saggese, Fabio [3 ]
Lu, Xinhua
Wang, Zhongyong [1 ]
Zhu, Zhengyu [1 ,4 ]
机构
[1] Zhengzhou Univ, Sch Elect & Informat Engn, Zhengzhou 450001, Peoples R China
[2] Nanyang Inst Technol, Coll Informat Engn, Nanyang 473000, Peoples R China
[3] Aalborg Univ, Dept Elect Syst, DK-9220 Aalborg, Denmark
[4] Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210018, Peoples R China
关键词
Massive MIMO; OFDM; channel estimation; channel probability model;
D O I
10.1109/LCOMM.2023.3268819
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
In this letter, we propose the Bernoulli two-state Gaussian mixture (B-TSGM) probability model to characterize the angle-delay domain (ADD) channel of the massive multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) system. Based on the hybrid message passing (HMP) rule, we design the HMP-B-TSGM channel estimation algorithm under the structured turbo-compressed sensing (STCS) framework. Simulation results show that the considered model better captures the channel characteristics, and the proposed algorithm outperforms the state-of-the-art methods under a wide range of simulation settings while having the same complexity.
引用
收藏
页码:1584 / 1588
页数:5
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