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http://dx.doi.org/10.3837/tiis.2021.05.019

Coordinated Millimeter Wave Beam Selection Using Fingerprint for Cellular-Connected Unmanned Aerial Vehicle  

Moon, Sangmi (Department of IT Artificial Intelligence, Korea Nazarene University)
Kim, Hyeonsung (Department of Electronic Engineering, Chonnam National University)
You, Young-Hwan (Department of Computer Engineering, Sejong University)
Kim, Cheol Hong (School of Computer Science and Engineering, Soongsil University)
Hwang, Intae (Department of Electronic Engineering and Department of ICT Convergence System Engineering, College of Engineering, Chonnam National University)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.15, no.5, 2021 , pp. 1929-1943 More about this Journal
Abstract
Millimeter wave (mmWave) communication based on the wide bandwidth of >28 GHz is one of the key technologies for cellular-connected unmanned aerial vehicles (UAVs). The selection of mmWave beams in such cellular-connected UAVs is challenging and critical, especially when downlink transmissions toward aerial user equipment (UE) suffer from poor signal-to-interference-plus-noise ratio (SINR) more often than their terrestrial counterparts. This study proposed a coordinated mmWave beam selection scheme using fingerprint for cellular-connected UAV. The scheme comprises fingerprint database configuration and coordinated beam selection. In the fingerprint database configuration, the best beam index from the serving cell and interference beam indexes from neighboring cells are stored. In the coordinated beam selection, the best and interference beams are determined using the fingerprint database information instead of performing an exhaustive search, and the coordinated beam transmission improves the SINR for aerial UEs. System-level simulations assess the UAV effect based on the third-generation partnership project-new radio mmWave and UAV channel models. Simulation results show that the proposed scheme can reduce the overhead of exhaustive search and improve the SINR and spectral efficiency.
Keywords
Coordinated beam selection; fingerprint; mmWave; UAV;
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