Ground-to-UAV Communication Network: Stochastic Geometry-based Performance Analysis

Yalin LIU, Hong-ning DAI, Muhammad IMRAN, Nidal NASSER

Research output: Other Conference ContributionsConference Paper (other)Researchpeer-review

Abstract

In this paper, we employ stochastic geometry to analyze ground-to-unmanned aerial vehicle (UAV) communications. We consider multiple UAVs to provide user-equipments (UEs) with uplink transmissions, where the distribution of UEs follows the Poisson Cluster process (PCP) and each UAV is dedicated to a specific cluster. In particular, we characterize the Laplace transform of the interference caused by multiple UEs in terms of the distribution of UEs as well as the transmission probability of each UE. We then derive analytical expressions of the successful transmission probability. We next conduct a comprehensive numerical analysis with consideration of different system parameters. The results show that four factors (i.e., the geographical surroundings, the transmission powers, the Signal-to-Interference-plus-Noise Ratio (SINR) thresholds, and the UAV height) have main influences on ground-to-UAV communications.
Original languageEnglish
Number of pages6
DOIs
Publication statusPublished - Jun 2021
Externally publishedYes
EventICC 2021 - IEEE International Conference on Communications - Montreal, QC, Canada
Duration: 14 Jun 202123 Jun 2021

Conference

ConferenceICC 2021 - IEEE International Conference on Communications
Period14/06/2123/06/21

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