Joint User Grouping and Beam Selection for Beamspace mmWave Multi-User MIMO System

被引：5

作者：

Sun, Jintian ^{[1
]}

Jia, Min ^{[1
]}

Guo, Qing ^{[1
]}

Gu, Xuemai ^{[1
]}

机构：

[1] Harbin Inst Technol, Sch Elect & Informat Engn, Harbin 150008, Peoples R China

来源：

IEEE COMMUNICATIONS LETTERS | 2022年 / 26卷 / 05期

关键词：

Optimized production technology; Antenna arrays; Complexity theory; Signal to noise ratio; Precoding; Optimization; Lenses; Massive MIMO; lens antenna array; beam selection; user grouping; deep learning; ALGORITHMS;

D O I：

10.1109/LCOMM.2022.3158665

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

Lens antenna arrays based beamspace millimeter-wave multi-user massive MIMO (B-MIMO) can significantly improve energy efficiency without significant loss of spectral efficiency (SE), which is considered as a highly expected technology for future wireless communication networks. Motivated by the requirement of reducing SE loss by efficient user grouping (UG) and beam selection (BS), a joint user grouping and beam selection algorithm is studied. Specifically, a local search based BS algorithm is proposed by proving the convexity of the BS problem after relaxing the constraints. Moreover, a deep learning based UG algorithm is proposed by equivalently transforming the UG problem into a classification problem. The results of theoretical analysis and numerical simulation show that the proposed algorithms can be more closely with the performance of the exhaustive search algorithm and the complexity is lower than that of the traditional algorithms.

引用

页码：1170 / 1174

页数：5

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