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http://dx.doi.org/10.3837/tiis.2022.04.013

Low Complexity Hybrid Precoding in Millimeter Wave Massive MIMO Systems  

Cheng, Tongtong (China Academy of Information and Communications Technology)
He, Yigang (Hefei University of Technology)
Wu, Yuting (Hefei University of Technology)
Ning, Shuguang (Hefei University of Technology)
Sui, Yongbo (Hefei University of Technology)
Huang, Yuan (Hefei University of Technology)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.16, no.4, 2022 , pp. 1330-1350 More about this Journal
Abstract
As a preprocessing operation of transmitter antennas, the hybrid precoding is restricted by the limited computing resources of the transmitter. Therefore, this paper proposes a novel hybrid precoding that guarantees the communication efficiency with low complexity and a fast computational speed. First, the analog and digital precoding matrix is derived from the maximum eigenvectors of the channel matrix in the sub-connected architecture to maximize the communication rate. Second, the extended power iteration (EPI) is utilized to obtain the maximum eigenvalues and their eigenvectors of the channel matrix, which reduces the computational complexity caused by the singular value decomposition (SVD). Third, the Aitken acceleration method is utilized to further improve the convergence rate of the EPI algorithm. Finally, the hybrid precoding based on the EPI method and the Aitken acceleration algorithm is evaluated in millimeter-wave (mmWave) massive multiple-input and multiple-output (MIMO) systems. The experimental results show that the proposed method can reduce the computational complexity with the high performance in mmWave massive MIMO systems. The method has the wide application prospect in future wireless communication systems.
Keywords
Power iteration; Aitken acceleration; extended power iteration; hybrid precoding; millimeter wave; massive MIMO systems;
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Times Cited By KSCI : 2  (Citation Analysis)
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