Recent developments in robotics and communication technologies are paving the way towards the use of Unmanned Aerial Vehicles (UAVs) to provide ubiquitous connectivity in public safety scenarios or in remote areas. The millimeter wave (mmWave) spectrum, in particular, has gained momentum since the huge amount of free spectrum available at such frequencies can yield very high data rates. In the UAV context, however, mmWave operations may incur severe signal attenuation and sensitivity to blockage, especially considering the very long trans- mission distances involved. In this paper, we present a tractable stochastic analysis to characterize the coverage probability of UAV stations operating at mmWaves. We exemplify some of the trade-offs to be considered when designing solutions for millimeter wave (mmWave) scenarios, such as the beamforming configuration, and the UAV altitude and deployment.

Coverage Analysis of UAVs in Millimeter Wave Networks: A Stochastic Geometry Approach

Matilde Boschiero;Marco Giordani;Michele Polese;Michele Zorzi
2020

Abstract

Recent developments in robotics and communication technologies are paving the way towards the use of Unmanned Aerial Vehicles (UAVs) to provide ubiquitous connectivity in public safety scenarios or in remote areas. The millimeter wave (mmWave) spectrum, in particular, has gained momentum since the huge amount of free spectrum available at such frequencies can yield very high data rates. In the UAV context, however, mmWave operations may incur severe signal attenuation and sensitivity to blockage, especially considering the very long trans- mission distances involved. In this paper, we present a tractable stochastic analysis to characterize the coverage probability of UAV stations operating at mmWaves. We exemplify some of the trade-offs to be considered when designing solutions for millimeter wave (mmWave) scenarios, such as the beamforming configuration, and the UAV altitude and deployment.
Proceedings of 16th International Wireless Communications & Mobile Computing Conference (IWCMC 2020)
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11577/3334570
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