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

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

5 Citations (Scopus)

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
Title of host publication	ICC 2021 - IEEE International Conference on Communications, Proceedings
Publisher	IEEE
Pages	1-6
Number of pages	6
ISBN (Electronic)	9781728171227
ISBN (Print)	9781728171234
DOIs	https://doi.org/10.1109/ICC42927.2021.9500746
Publication status	Published - Jun 2021
Event	2021 IEEE International Conference on Communications, ICC 2021 - Virtual, Online, Montreal, Canada Duration: 14 Jun 2021 → 23 Jun 2021 https://ieeexplore.ieee.org/xpl/conhome/9500243/proceeding

Publication series

Name	IEEE International Conference on Communications
ISSN (Print)	1550-3607
ISSN (Electronic)	1938-1883

Conference

Conference	2021 IEEE International Conference on Communications, ICC 2021
Country/Territory	Canada
City	Montreal
Period	14/06/21 → 23/06/21
Internet address	https://ieeexplore.ieee.org/xpl/conhome/9500243/proceeding

Scopus Subject Areas

Computer Networks and Communications
Electrical and Electronic Engineering

Access to Document

10.1109/ICC42927.2021.9500746

Cite this

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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 Dai, {Hong Ning} 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.; 2021 IEEE International Conference on Communications, ICC 2021 ; Conference date: 14-06-2021 Through 23-06-2021",

year = "2021",

month = jun,

doi = "10.1109/ICC42927.2021.9500746",

language = "English",

isbn = "9781728171234",

series = "IEEE International Conference on Communications",

publisher = "IEEE",

pages = "1--6",

booktitle = "ICC 2021 - IEEE International Conference on Communications, Proceedings",

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url = "https://ieeexplore.ieee.org/xpl/conhome/9500243/proceeding",

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Liu, Y, Dai, HN, Imran, M & Nasser, N 2021, Ground-to-UAV Communication Network: Stochastic Geometry-based Performance Analysis. in ICC 2021 - IEEE International Conference on Communications, Proceedings. IEEE International Conference on Communications, IEEE, pp. 1-6, 2021 IEEE International Conference on Communications, ICC 2021, Montreal, Canada, 14/06/21. https://doi.org/10.1109/ICC42927.2021.9500746

Ground-to-UAV Communication Network: Stochastic Geometry-based Performance Analysis. / Liu, Yalin; Dai, Hong Ning; Imran, Muhammad et al.
ICC 2021 - IEEE International Conference on Communications, Proceedings. IEEE, 2021. p. 1-6 (IEEE International Conference on Communications).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

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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.

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

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