Particle swarm optimization based beamforming in massive MIMO systems

3Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.

Abstract

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.

Cite

CITATION STYLE

APA

Kareem, T. A., Hussain, M. A., & Jabbar, M. K. (2020). Particle swarm optimization based beamforming in massive MIMO systems. International Journal of Interactive Mobile Technologies, 14(5), 176–192. https://doi.org/10.3991/IJIM.V14I05.13701

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free