Particle Swarm Optimization Based Beamforming in Massive MIMO Systems

Particle Swarm Optimization Based Beamforming in Massive MIMO Systems

Millimeter-wave

Beamforming

Massive MIMO

PSO optimization

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.  

Kareem, Thaar A.

Alaa Hussain, Maab

Kareem Jabbar, Mays

International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 05 (2020); pp. 176-192

1865-7923

International Association of Online Engineering (IAOE), Vienna, Austria

2020-04-07

Copyright (c) 2020 Thaar A. Kareem, Maab alaa, Mays Kareem, Haider Alrikabi

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eng

info:eu-repo/semantics/article

info:eu-repo/semantics/publishedVersion

Peer-reviewed Article