基于奇异值分解和粒子群优化方法的5G毫米波系统三维波束形成

Osama Alluhaibi, Manish Nair, Amjed Hazzaa, Aza Mihbarey, Jiangzhou Wang
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引用次数: 8

摘要

毫米波(mmWave)系统是第五代(5G)移动网络的拟议解决方案之一。然而,由于频率较高,毫米波系统会经历强烈的路径损耗。为了解决这个问题,这种系统需要窄波束模式,以减少由于高路径损耗而导致的毫米波信号能量损失。在部署之前需要解决的一个重大挑战是设计三维(3D)波束形成算法,该算法需要具有方向性。在本文中,我们首先提出了两种三维波束形成算法,目的是在方位角和仰角平面上同时跟踪用户。我们提出的波束形成算法基于奇异值分解(SVD)和粒子群优化(PSO)的原理。此外,这些波束形成算法被设计成具有有限或可忽略的侧瓣,这对在同一小区中操作的其他用户造成的干扰较小。为了实现这一目标,采用了Kaiser Bessel (KB)滤波器,该滤波器有助于减轻合成波束图中的侧瓣。根据我们的分析,我们获得了一些有价值的见解。所提出的算法在实现相当大的容量和较低的侧波方面表现良好。
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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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