arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2007.15088cs.ITeess.SPmath.IT
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未来高海拔平台站(HAPS)网络的展望和框架

A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future

Gunes Kurt, Mohammad G. Khoshkholgh, Safwan Alfattani, Ahmed Ibrahim, Tasneem S. J. Darwish, Md Sahabul Alam, Halim Yanikomeroglu, Abbas Yongacoglu

摘要:

高海拔平台站(HAPS)是在平流层中海拔约20 km处运行的网络节点,并且有助于提供通信服务。在自主航空电子设备、阵列天线、太阳能电池板效率水平和电池能量密度领域的技术创新的推动下,在蓬勃发展的行业生态系统的推动下,HAPS已成为下一代无线网络不可或缺的组成部分。在这篇文章中,我们提供了一个愿景和框架的HAPS网络的未来支持的全面和国家的最先进的文献综述。我们强调了HAPS系统未实现的潜力,并详细阐述了其独特的能力,为大都市地区。讨论了HAPS能量和有效载荷系统的最新进展和有前途的技术。提出了将新兴的可重构智能表面(RSS)技术集成到HAPS系统的通信有效载荷中,以提供具有成本效益的部署。HAPS系统中的无线电资源管理的详细概述与协同物理层技术,包括快于奈奎斯特(FTN)信令。描述了HAPS系统中切换管理的许多方面。强调了人工智能在HAPS中的显著贡献,包括机器学习在设计、拓扑管理、切换和资源分配方面的作用。我们提供的文献的广泛概述对于证实我们的愿景至关重要,该愿景描述了未来10年(下一代网络)以及随后10年(下一代网络)的预期部署机会和挑战。

英文摘要:

A High Altitude Platform Station (HAPS) is a network node that operates in the stratosphere at an of altitude around 20 km and is instrumental for providing communication services. Precipitated by technological innovations in the areas of autonomous avionics, array antennas, solar panel efficiency levels, and battery energy densities, and fueled by flourishing industry ecosystems, the HAPS has emerged as an indispensable component of next-generations of wireless networks. In this article, we provide a vision and framework for the HAPS networks of the future supported by a comprehensive and state-of-the-art literature review. We highlight the unrealized potential of HAPS systems and elaborate on their unique ability to serve metropolitan areas. The latest advancements and promising technologies in the HAPS energy and payload systems are discussed. The integration of the emerging Reconfigurable Smart Surface (RSS) technology in the communications payload of HAPS systems for providing a cost-effective deployment is proposed. A detailed overview of the radio resource management in HAPS systems is presented along with synergistic physical layer techniques, including Faster-Than-Nyquist (FTN) signaling. Numerous aspects of handoff management in HAPS systems are described. The notable contributions of Artificial Intelligence (AI) in HAPS, including machine learning in the design, topology management, handoff, and resource allocation aspects are emphasized. The extensive overview of the literature we provide is crucial for substantiating our vision that depicts the expected deployment opportunities and challenges in the next 10 years (next-generation networks), as well as in the subsequent 10 years (next-next-generation networks).

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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