Optimal SSB Beam Planning and UAV Cell Selection for 5G Connectivity on Aerial Highways
Matteo Bernabe, David Lopez-Perez, Nicola Piovesan, Giovanni Geraci,, and David Gesbert

TL;DR
This paper proposes an optimized cell association and SSB beam planning method for UAVs on aerial highways in 5G networks, significantly enhancing UAV data rates while maintaining ground user performance.
Contribution
It introduces a novel cell selection metric and an SSB beam planning algorithm tailored for UAVs in 5G, addressing interference and spatial multiplexing challenges.
Findings
UAV data rates improved up to four times
Effective UAV and ground user coexistence achieved
New cell selection metric outperforms classical RSRP-based methods
Abstract
In this article, we introduce a method to optimize 5G massive multiple-input multiple-output (mMIMO) connectivity for unmanned aerial vehicles (UAVs) on aerial highways through strategic cell association. UAVs operating in 3D space encounter distinct channel conditions compared to traditional ground user equipment (gUE); under the typical line of sight (LoS) condition, UAVs perceive strong reference signal received power (RSRP) from multiple cells within the network, resulting in a large set of suitable serving cell candidates and in low signal-to-interference-plus-noise ratio (SINR) due to high interference levels. Additionally, a downside of aerial highways is to pack possibly many UAVs along a small portion of space which, when taking into account typical LoS propagation conditions, results in high channel correlation and severely limits spatial multiplexing capabilities. In this…
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Taxonomy
TopicsUAV Applications and Optimization · Distributed Control Multi-Agent Systems · Robotic Path Planning Algorithms
