10th EAI International Conference on Communications and Networking in China

Research Article

PSO-based Vertical Beamforming for 3D Massive MIMO Systems in 5G

  • @INPROCEEDINGS{10.4108/eai.15-8-2015.2260555,
        author={Yuan Zhou and Shaozhen Guo},
        title={PSO-based Vertical Beamforming for 3D Massive MIMO Systems in 5G},
        proceedings={10th EAI International Conference on Communications and Networking in China},
        publisher={IEEE},
        proceedings_a={CHINACOM},
        year={2015},
        month={9},
        keywords={3d massive mimo vertical beamforming downtilts adjustment power allocation pso},
        doi={10.4108/eai.15-8-2015.2260555}
    }
    
  • Yuan Zhou
    Shaozhen Guo
    Year: 2015
    PSO-based Vertical Beamforming for 3D Massive MIMO Systems in 5G
    CHINACOM
    IEEE
    DOI: 10.4108/eai.15-8-2015.2260555
Yuan Zhou1,*, Shaozhen Guo1
  • 1: RCDCT, School of Information and Electronics, Beijing Institute of Technology, Beijing, China.
*Contact email: zhouyuanbit@gmail.com

Abstract

In this paper, we consider the vertical beamforming in the downlink of a three dimensional (3D) massive multiple-input multiple-output (MIMO) system. Two beams are partitioned through dynamic vertical beamforming with two specific downtilts. Taking these users' specific downtilts into consideration, the objective of this scheme is to maximize cell spectral efficiency by adjusting the powers and downtilts of the two vertical beams, subject to BS power consumption and downtilt constraints. To solve this problem, a particle swarm optimization (PSO) based vertical beamforming optimization algorithm is proposed, in which the powers and the downtilts are represented by the positions of particles; and the update direction guided the movement are mapped to the velocity. We define the cell spectral efficiency as the fitness function. By iteratively updating the positions and velocities of the particles according to some principles considering all constrains, the optimum solution can be obtained to maximize the fitness function. Simulation results show that a high cell spectral efficiency can be achieved with a low complexity by the proposed algorithm.