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Link Budget Analysis for Reconfigurable Smart Surfaces in Aerial Platforms

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posted on 31.03.2021, 04:28 by SAFWAN ALFATTANI, Wael Jaafar, Yassine Hmamouche, Halim Yanikomeroglu, Abbas Yongacoglu
Non-terrestrial networks, including Unmanned Aerial Vehicles (UAVs), High Altitude Platform Station (HAPS) and Low Earth Orbiting (LEO) satellites, are expected to have a pivotal role in the sixth generation wireless networks. With their inherent features such as flexible placement, wide footprint, and preferred channel conditions, they can tackle several challenges in current terrestrial networks. However, their successful and widespread adoption relies on energy-efficient on-board communication systems. In this context, the integration of Reconfigurable Smart Surfaces (RSS) into aerial platforms is envisioned as a key enabler of energy-efficient and cost-effective deployments of aerial platforms. Indeed, RSS consist of low-cost reflectors capable of smartly directing signals in a nearly passive way. We investigate in this paper the link budget of RSS-assisted communications under the two discussed RSS reflection paradigms in the literature, namely the specular and the scattering reflection paradigm types. Specifically, we analyze the characteristics of RSS-equipped aerial platforms and compare their communication performance with that of RSS-assisted terrestrial networks, using standardized channel models. In addition, we derive the optimal aerial platforms placements under both reflection paradigms. The obtained results provide important insights for the design of RSS-assisted communications. For instance, given that a HAPS has a large RSS surface, it provides superior link budget performance in most studied scenarios. In contrast, the limited RSS area on UAVs and the large propagation loss in LEO satellite communications make them unfavorable candidates for supporting terrestrial users. Finally, the optimal location of the RSS-equipped platform may depend on the platform’s altitude, coverage footprint, and type of environment.

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Email Address of Submitting Author

smalfattani@kau.edu.sa

ORCID of Submitting Author

0000-0001-8417-4363

Submitting Author's Institution

king AbdulAziz University

Submitting Author's Country

Saudi Arabia

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