Optimal UAV-Relay Positioning and Transmit Power Allocation in ISAC-Based A2G Networks

Ji Min Park; Junseok Lee; Heejung Yu

doi:10.1109/CCNC54725.2025.10976176

Optimal UAV-Relay Positioning and Transmit Power Allocation in ISAC-Based A2G Networks

Ji Min Park
, Junseok Lee
, Heejung Yu

Korea University (SEJONG)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

Recently, interest in communication services using unmanned aerial vehicles (UAVs) and integrated sensing and communication (ISAC) systems that utilize radar and communication simultaneously has been increasing rapidly. Wireless communications through UAVs have the advantage of easily securing a line-of-sight (LoS) channel with ground users due to their flexibility in deployment. ISAC systems can use bandwidth efficiently by combining radar and communication into a single system. In this study, communication and radar performance were optimized in a UAV-relay-based ISAC system using a single communication waveform through multi-agent Q-learning. The convergence and performance of the proposed Q-learning algorithm were confirmed through simulations.

Original language	English
Title of host publication	2025 IEEE 22nd Consumer Communications and Networking Conference, CCNC 2025
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798331508050
DOIs	https://doi.org/10.1109/CCNC54725.2025.10976176
Publication status	Published - 2025
Event	22nd IEEE Consumer Communications and Networking Conference, CCNC 2025 - Las Vegas, United States Duration: 2025 Jan 10 → 2025 Jan 13

Publication series

Name	Proceedings - IEEE Consumer Communications and Networking Conference, CCNC
ISSN (Print)	2331-9860

Conference

Conference	22nd IEEE Consumer Communications and Networking Conference, CCNC 2025
Country/Territory	United States
City	Las Vegas
Period	25/1/10 → 25/1/13

Bibliographical note

Publisher Copyright:
© 2025 IEEE.

Keywords

A2G Network
ISAC
Q-learning
UAV

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Computer Networks and Communications
Artificial Intelligence
Electrical and Electronic Engineering

Access to Document

10.1109/CCNC54725.2025.10976176

Cite this

Park, J. M., Lee, J., & Yu, H. (2025). Optimal UAV-Relay Positioning and Transmit Power Allocation in ISAC-Based A2G Networks. In 2025 IEEE 22nd Consumer Communications and Networking Conference, CCNC 2025 (Proceedings - IEEE Consumer Communications and Networking Conference, CCNC). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CCNC54725.2025.10976176

Optimal UAV-Relay Positioning and Transmit Power Allocation in ISAC-Based A2G Networks. / Park, Ji Min; Lee, Junseok; Yu, Heejung.
2025 IEEE 22nd Consumer Communications and Networking Conference, CCNC 2025. Institute of Electrical and Electronics Engineers Inc., 2025. (Proceedings - IEEE Consumer Communications and Networking Conference, CCNC).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Park, JM, Lee, J & Yu, H 2025, Optimal UAV-Relay Positioning and Transmit Power Allocation in ISAC-Based A2G Networks. in 2025 IEEE 22nd Consumer Communications and Networking Conference, CCNC 2025. Proceedings - IEEE Consumer Communications and Networking Conference, CCNC, Institute of Electrical and Electronics Engineers Inc., 22nd IEEE Consumer Communications and Networking Conference, CCNC 2025, Las Vegas, United States, 25/1/10. https://doi.org/10.1109/CCNC54725.2025.10976176

@inproceedings{d0f216c09ce6453f974e0f0466ab634c,

title = "Optimal UAV-Relay Positioning and Transmit Power Allocation in ISAC-Based A2G Networks",

abstract = "Recently, interest in communication services using unmanned aerial vehicles (UAVs) and integrated sensing and communication (ISAC) systems that utilize radar and communication simultaneously has been increasing rapidly. Wireless communications through UAVs have the advantage of easily securing a line-of-sight (LoS) channel with ground users due to their flexibility in deployment. ISAC systems can use bandwidth efficiently by combining radar and communication into a single system. In this study, communication and radar performance were optimized in a UAV-relay-based ISAC system using a single communication waveform through multi-agent Q-learning. The convergence and performance of the proposed Q-learning algorithm were confirmed through simulations.",

keywords = "A2G Network, ISAC, Q-learning, UAV",

author = "Park, \{Ji Min\} and Junseok Lee and Heejung Yu",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 22nd IEEE Consumer Communications and Networking Conference, CCNC 2025 ; Conference date: 10-01-2025 Through 13-01-2025",

year = "2025",

doi = "10.1109/CCNC54725.2025.10976176",

language = "English",

series = "Proceedings - IEEE Consumer Communications and Networking Conference, CCNC",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2025 IEEE 22nd Consumer Communications and Networking Conference, CCNC 2025",

}

TY - GEN

T1 - Optimal UAV-Relay Positioning and Transmit Power Allocation in ISAC-Based A2G Networks

AU - Park, Ji Min

AU - Lee, Junseok

AU - Yu, Heejung

PY - 2025

Y1 - 2025

N2 - Recently, interest in communication services using unmanned aerial vehicles (UAVs) and integrated sensing and communication (ISAC) systems that utilize radar and communication simultaneously has been increasing rapidly. Wireless communications through UAVs have the advantage of easily securing a line-of-sight (LoS) channel with ground users due to their flexibility in deployment. ISAC systems can use bandwidth efficiently by combining radar and communication into a single system. In this study, communication and radar performance were optimized in a UAV-relay-based ISAC system using a single communication waveform through multi-agent Q-learning. The convergence and performance of the proposed Q-learning algorithm were confirmed through simulations.

AB - Recently, interest in communication services using unmanned aerial vehicles (UAVs) and integrated sensing and communication (ISAC) systems that utilize radar and communication simultaneously has been increasing rapidly. Wireless communications through UAVs have the advantage of easily securing a line-of-sight (LoS) channel with ground users due to their flexibility in deployment. ISAC systems can use bandwidth efficiently by combining radar and communication into a single system. In this study, communication and radar performance were optimized in a UAV-relay-based ISAC system using a single communication waveform through multi-agent Q-learning. The convergence and performance of the proposed Q-learning algorithm were confirmed through simulations.

KW - A2G Network

KW - ISAC

KW - Q-learning

KW - UAV

UR - https://www.scopus.com/pages/publications/105005138393

U2 - 10.1109/CCNC54725.2025.10976176

DO - 10.1109/CCNC54725.2025.10976176

M3 - Conference contribution

AN - SCOPUS:105005138393

T3 - Proceedings - IEEE Consumer Communications and Networking Conference, CCNC

BT - 2025 IEEE 22nd Consumer Communications and Networking Conference, CCNC 2025

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 22nd IEEE Consumer Communications and Networking Conference, CCNC 2025

Y2 - 10 January 2025 through 13 January 2025

ER -

Optimal UAV-Relay Positioning and Transmit Power Allocation in ISAC-Based A2G Networks

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this