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

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

doi:10.1109/ICC42927.2021.9500746

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

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

Research output: Other Conference Contributions › Conference Paper (other) › Research › peer-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 language	English
Number of pages	6
DOIs	https://doi.org/10.1109/ICC42927.2021.9500746
Publication status	Published - Jun 2021
Externally published	Yes
Event	ICC 2021 - IEEE International Conference on Communications - Montreal, QC, Canada Duration: 14 Jun 2021 → 23 Jun 2021

Conference

Conference	ICC 2021 - IEEE International Conference on Communications
Period	14/06/21 → 23/06/21

Bibliographical note

Funding Information:
This paper was partially supported by Macao Science and Technology Development Fund under Grant No. 0026/2018/A1. The authors would like to thank Alfaisal University for funding and supporting this work through the Internal Research Grant 21207.

Publisher Copyright:
© 2021 IEEE.

Access to Document

10.1109/ICC42927.2021.9500746

https://ieeexplore.ieee.org/document/9500746/

Cite this

@conference{ff2caa72cda8488190412c19a2fb1c44,

title = "Ground-to-UAV Communication Network: Stochastic Geometry-based Performance Analysis",

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.",

author = "Yalin LIU and Hong-ning DAI and Muhammad IMRAN and Nidal NASSER",

note = "Funding Information: This paper was partially supported by Macao Science and Technology Development Fund under Grant No. 0026/2018/A1. The authors would like to thank Alfaisal University for funding and supporting this work through the Internal Research Grant 21207. Publisher Copyright: {\textcopyright} 2021 IEEE.; ICC 2021 - IEEE International Conference on Communications ; Conference date: 14-06-2021 Through 23-06-2021",

year = "2021",

month = jun,

doi = "10.1109/ICC42927.2021.9500746",

language = "English",

}

TY - CONF

T1 - Ground-to-UAV Communication Network: Stochastic Geometry-based Performance Analysis

AU - LIU, Yalin

AU - DAI, Hong-ning

AU - IMRAN, Muhammad

AU - NASSER, Nidal

N1 - Funding Information: This paper was partially supported by Macao Science and Technology Development Fund under Grant No. 0026/2018/A1. The authors would like to thank Alfaisal University for funding and supporting this work through the Internal Research Grant 21207. Publisher Copyright: © 2021 IEEE.

PY - 2021/6

Y1 - 2021/6

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85115715486&partnerID=8YFLogxK

U2 - 10.1109/ICC42927.2021.9500746

DO - 10.1109/ICC42927.2021.9500746

M3 - Conference Paper (other)

T2 - ICC 2021 - IEEE International Conference on Communications

Y2 - 14 June 2021 through 23 June 2021

ER -

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

Abstract

Conference

Bibliographical note

Access to Document

Other files and links

Fingerprint

Cite this