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IEICE TRANSACTIONS on Communications

Open Access
Low-Complexity Hybrid Precoding Based on PAST for Millimeter Wave Massive MIMO System

Rui JIANG, Xiao ZHOU, You Yun XU, Li ZHANG

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Summary :

Millimeter wave (mmWave) massive Multiple-Input Multiple-Output (MIMO) systems generally adopt hybrid precoding combining digital and analog precoder as an alternative to full digital precoding to reduce RF chains and energy consumption. In order to balance the relationship between spectral efficiency, energy efficiency and hardware complexity, the hybrid-connected system structure should be adopted, and then the solution process of hybrid precoding can be simplified by decomposing the total achievable rate into several sub-rates. However, the singular value decomposition (SVD) incurs high complexity in calculating the optimal unconstrained hybrid precoder for each sub-rate. Therefore, this paper proposes PAST, a low complexity hybrid precoding algorithm based on projection approximate subspace tracking. The optimal unconstrained hybrid precoder of each sub-rate is estimated with the PAST algorithm, which avoids the high complexity process of calculating the left and right singular vectors and singular value matrix by SVD. Simulations demonstrate that PAST matches the spectral efficiency of SVD-based hybrid precoding in full-connected (FC), hybrid-connected (HC) and sub-connected (SC) system structure. Moreover, the superiority of PAST over SVD-based hybrid precoding in terms of complexity and increases with the number of transmitting antennas.

Publication
IEICE TRANSACTIONS on Communications Vol.E105-B No.10 pp.1192-1201
Publication Date
2022/10/01
Publicized
2022/04/21
Online ISSN
1745-1345
DOI
10.1587/transcom.2021EBP3188
Type of Manuscript
PAPER
Category
Fundamental Theories for Communications

Authors

Rui JIANG
  Nanjing University of Posts and Telecommunications
Xiao ZHOU
  Nanjing University of Posts and Telecommunications
You Yun XU
  Nanjing University of Posts and Telecommunications
Li ZHANG
  Nanjing Forestry University

Keyword