Particle swarm optimization based beamforming in massive MIMO systems

被引：1
|
作者：
Kareem T.A. [1 ]
Hussain M.A. [1 ]
Jabbar M.K. [1 ]
机构：
[1] University of Misan, Misan
来源：
International Journal of Interactive Mobile Technologies | 2020年 / 14卷 / 05期
关键词：
Beamforming; Massive MIMO; Millimeter-wave; PSO optimization;
D O I：
10.3991/IJIM.V14I05.13701
中图分类号：
学科分类号：
摘要：
This research puts forth an optimization-based analog beamforming scheme for millimeter-wave (mmWave) massive MIMO systems. Main aim is to optimize the combination of analog precoder / combiner matrices for the purpose of getting near-optimal performance. Codebook-based analog beamforming with transmit precoding and receive combining serves the purpose of compensating the severe attenuation of mmWave signals. The existing and traditional beamforming schemes involve a complex search for the best pair of analog precoder / combiner matrices from predefined codebooks. In this research, we have solved this problem by using Particle Swarm Optimization (PSO) to find the best combination of precoder / combiner matrices among all possible pairs with the objective of achieving near-optimal performance with regard to maximum achievable rate. Experiments prove the robustness of the proposed approach in comparison to the benchmarks considered. © 2020 International Association of Online Engineering.
引用
收藏
页码：176 / 192
页数：16
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