用于高空平台站 (HAPS) 的半球形天线阵列架构,以提供统一容量

Omid Abbasi, Halim Yanikomeroglu, Georges Kaddoum
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引用次数: 0

摘要

本文介绍了一种为高空平台站(HAPS)设计的新型半球形天线阵列(HAA)。用于高空平台站的传统矩形天线阵列的一个重要局限是其天线元件方向向下,导致远距离用户的增益较低。圆柱形天线阵列的引入缓解了这一缺点,但其天线元件面向地平线,导致位于 HAPS 下方的用户无法获得最佳增益。为了应对这些挑战,我们在本研究中引入了 HAA。HAA 的天线元件战略性地分布在半球表面,以确保每个用户直接对准特定的天线元件。为了最大限度地提高用户的最小信噪比(SINR),我们提出了一个优化问题。在进行模拟波束成形后,我们引入了一种天线选择算法,并证明当为每个用户选择大量天线元件时,该方法可达到最佳效果。此外,我们还采用了二分法来确定每个用户的最佳功率分配。我们的仿真结果令人信服地证明,所提出的 HAA 性能优于传统阵列,并能在整个覆盖区域提供均匀的速率。在20~\mathrm{MHz}$通信带宽和50~\mathrm{dBm}$总功率条件下,拟议方法的总速率达到14~\mathrm{Gbps}$。
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Hemispherical Antenna Array Architecture for High-Altitude Platform Stations (HAPS) for Uniform Capacity Provision
In this paper, we present a novel hemispherical antenna array (HAA) designed for high-altitude platform stations (HAPS). A significant limitation of traditional rectangular antenna arrays for HAPS is that their antenna elements are oriented downward, resulting in low gains for distant users. Cylindrical antenna arrays were introduced to mitigate this drawback; however, their antenna elements face the horizon leading to suboptimal gains for users located beneath the HAPS. To address these challenges, in this study, we introduce our HAA. An HAA's antenna elements are strategically distributed across the surface of a hemisphere to ensure that each user is directly aligned with specific antenna elements. To maximize users minimum signal-to-interference-plus-noise ratio (SINR), we formulate an optimization problem. After performing analog beamforming, we introduce an antenna selection algorithm and show that this method achieves optimality when a substantial number of antenna elements are selected for each user. Additionally, we employ the bisection method to determine the optimal power allocation for each user. Our simulation results convincingly demonstrate that the proposed HAA outperforms the conventional arrays, and provides uniform rates across the entire coverage area. With a $20~\mathrm{MHz}$ communication bandwidth, and a $50~\mathrm{dBm}$ total power, the proposed approach reaches sum rates of $14~\mathrm{Gbps}$.
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