Joint Channel Estimation and Data Recovery for Millimeter Massive MIMO: Using Pilot to Capture Principal Components

被引:0
|
作者
Cai, Shusen [1 ]
Chen, Li [1 ]
Chen, Yunfei [2 ]
Yin, Huarui [1 ]
Wang, Weidong [1 ]
机构
[1] Univ Sci & Technol China, Dept Elect Engn & Informat Sci, Hefei 230027, Anhui, Peoples R China
[2] Univ Durham, Dept Engn, Durham DH1 3LE, England
关键词
Channel estimation; Millimeter wave communication; Estimation; Computational complexity; Vectors; Massive MIMO; Tensors; MmWave massive MIMO; joint channel estimation and data recovery; PF-assisted; principal components; LOW-COMPLEXITY; SYSTEMS; RECEIVER; CDMA;
D O I
10.1109/TCOMM.2024.3439448
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
Channel state information (CSI) is important to reap the full benefits of millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems. The traditional channel estimation methods using pilot frames (PF) lead to excessive overhead. To reduce the demand for PF, data frames (DF) can be adopted for joint channel estimation and data recovery. However, the computational complexity of the DF-based methods is prohibitively high. To reduce the computational complexity, we propose a joint channel estimation and data recovery (JCD) method assisted by a small number of PF for mmWave massive MIMO systems. The proposed method has two stages. In Stage 1, differing from the traditional PF-based methods used for precise estimation of channel parameters, the proposed PF-assisted method is utilized to narrow down the search range for the angle of arrival (AoA) of principal components (PC) of channels. In Stage 2, JCD is designed for parallel implementation based on the multi-user decoupling strategy. The theoretical analysis demonstrates that the PF-assisted JCD method can achieve equivalent performance to the Bayesian-optimal DF-based method, while greatly reducing the computational complexity. Simulation results are also presented to validate the analytical results.
引用
收藏
页码:781 / 799
页数:19
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