Particle Swarm Optimization Based Beamforming in Massive MIMO Systems

Authors

  • Thaar A. Kareem
  • Maab Alaa Hussain
  • Mays Kareem Jabbar

DOI:

https://doi.org/10.3991/ijim.v14i05.13701

Keywords:

Millimeter-wave, Beamforming, Massive MIMO, PSO optimization

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. 

 

Author Biographies

Thaar A. Kareem

 Electric Engineering College of Engineering ,University of Misan, Misan, Iraq

Maab Alaa Hussain

Civil Engineering College of Engineering ,University of Misan, Misan, Iraq

Mays Kareem Jabbar

 Electric Engineering College of Engineering ,University of Misan, Misan, Iraq

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Published

2020-04-07

How to Cite

Kareem, T. A., Alaa Hussain, M., & Kareem Jabbar, M. (2020). Particle Swarm Optimization Based Beamforming in Massive MIMO Systems. International Journal of Interactive Mobile Technologies (iJIM), 14(05), pp. 176–192. https://doi.org/10.3991/ijim.v14i05.13701

Issue

Vol. 14 No. 05 (2020)

Section

Papers

License

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