太赫兹空间信息网络的到达角估计

Hasan Nayir, G. Kurt, Ali̇ Görçi̇n
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引用次数: 1

摘要

太赫兹(THz)频率授权的空间信息网络(SINs)预计将在下一代无线空间网络中发挥至关重要的作用,因为太赫兹(THz)频率具有独特的传输特性和覆盖范围扩展能力,由于它们的高海拔。此外,利用太赫兹频率允许使用更多的带宽。然而,在这个频率范围内的通信需要付出极端路径损失的代价,特别是在低轨道实现SINs时。利用大量天线的高增益窄波束形成可以考虑克服这些频率上的大量损耗。因此,需要高精度和高效的到达角估计算法来实现成功的波束形成,并最终提高SINs的信噪比(SNR)。为此,我们提出在子阵列(AoSA)结构上使用两阶段gold-MUSIC算法进行AoA估计,与当前阵列相比,由于AoSA中的rf链减少,因此功耗更低,硬件复杂度更低。此外,我们还介绍了基于剩余多普勒频散的AoA估计性能分析,剩余多普勒频散是SINs的一个现实度量,因为在卫星瞬时快速运动变化的情况下,特别是在高频情况下,无法准确估计多普勒。结果表明,本文提出的两阶段gold-MUSIC方法在计算效率高的同时,能够提供准确的AoA估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Angle of Arrival Estimation for Terahertz-enabled Space Information Networks
Space information networks (SINs) empowered by Terahertz (THz) frequencies are expected to play a vital role in next-generation wireless space networks due to the unique transmission characteristics and coverage extension capabilities of SINs, owing to their high altitudes. Also, utilizing THz frequencies allows the usage of more bandwidth. However, communications in this frequency range come at the cost of extreme path loss, especially for low-orbit implementation of SINs. High gain narrow beamforming utilizing a large number of antennas can be considered to overcome substantial losses at these frequencies. Consequently, highly accurate and efficient angle of arrival (AoA) estimation algorithms are required to achieve successful beamforming and eventually to increase the signal-to-noise ratio (SNR) in SINs. To this end, we propose the utilization of a two-stage gold-MUSIC algorithm over an array of subarray (AoSA) structure for AoA estimation with lower power consumption and less hardware complexity compared to the contemporary arrays due to the reduced RF-chain in AoSA. Furthermore, we introduce an analysis of AoA estimation performance in terms of residual Doppler spread, which is a realistic metric for SINs since Doppler cannot be accurately estimated in the case of instantaneous rapid motional changes of satellites especially at high frequencies. Results show that the proposed two-staged gold-MUSIC method for AoSA provides accurate AoA estimation while being computationally efficient.
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