3D Beamforming for 5G Millimeter Wave Systems Using Singular Value Decomposition and Particle Swarm Optimization Approaches

Millimeter wave (mmWave) systems are one of the proposed solutions for the fifth generation (5G) mobile network. However, mmWave system experiences strong path loss due to higher frequencies. To solve this problem, such a system demands a narrow beampattern to reduce the loss of the mmWave signal energy due to the high path loss. One of the significant challenges to be addressed before their deployment is designing three dimensional (3D) beamforming algorithms, which are required to be directional. In this paper, we first propose two 3D beamforming algorithms with aim of tracking users in both the azimuth and elevation planes. Our proposed beamforming algorithms operates based on the principles of singular value decomposition (SVD) and particle swarm optimization (PSO). Furthermore, these beam-forming algorithms are designed to have limited or negligible side lobes, which cause less interference to the other users operating in the same cell. In order to achieve this objective, Kaiser Bessel (KB) filter is adopted which helps in mitigating side lobes in the synthesized beampattern. Based on our analysis, we gain some valuable insights. The proposed algorithms are shown to perform well in achieving considerable capacity and lower side lobs.

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3D Beamforming for 5G Millimeter Wave Systems Using Singular Value Decomposition and Particle Swarm Optimization Approaches

Semantic Scholar · Engineering · 2018

Abstract

Millimeter wave (mmWave) systems are one of the proposed solutions for the fifth generation (5G) mobile network. However, mmWave system experiences strong path loss due to higher frequencies. To solve this problem, such a system demands a narrow beampattern to reduce the loss of the mmWave signal energy due to the high path loss. One of the significant challenges to be addressed before their deployment is designing three dimensional (3D) beamforming algorithms, which are required to be directional. In this paper, we first propose two 3D beamforming algorithms with aim of tracking users in both the azimuth and elevation planes. Our proposed beamforming algorithms operates based on the principles of singular value decomposition (SVD) and particle swarm optimization (PSO). Furthermore, these beam-forming algorithms are designed to have limited or negligible side lobes, which cause less interference to the other users operating in the same cell. In order to achieve this objective, Kaiser Bessel (KB) filter is adopted which helps in mitigating side lobes in the synthesized beampattern. Based on our analysis, we gain some valuable insights. The proposed algorithms are shown to perform well in achieving considerable capacity and lower side lobs.

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