TY - GEN
T1 - Joint UAV-based Directional THz Communication and 3D Map Construction.
AU - Dabiri, Mohammad Taghi
AU - Hasna, Mazen O.
AU - Allhunibal, Saud
AU - Qaraqe, Khalid A.
N1 - DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.
PY - 2024/10/10
Y1 - 2024/10/10
N2 - This paper presents a novel approach for joint Terahertz (THz) communication and three-dimensional (3D) map reconstruction using an Unmanned Aerial Vehicle (UAV). Due to the need for precise mapping to provide Line-of-Sight (LoS) THz communication services, our approach leverages the UAV's trajectory to initiate the reconstruction and updating of the 3D environment in real-time. The UAV starts without any prior knowledge of the target area, establishing THz communications with users scattered among 3D obstacles. A comprehensive system model is developed, incorporating realistic antenna patterns, UAV oscillations, and received signal power modeling for accurate analysis. We establish an adaptive methodology for 3D environment modeling, dynamically constructing and refining a grid-based obstacle map. A dynamic algorithm for real-time 3D map reconstruction is implemented, utilizing received signal strengths to update the environmental model. Detailed simulations validate the effectiveness of our proposed methods, demonstrating significant improvements in computational efficiency and real-time decision-making in UAV-assisted communication networks. Our results highlight the potential of this joint approach in enhancing operational efficiency and communication reliability under varying environmental conditions.
AB - This paper presents a novel approach for joint Terahertz (THz) communication and three-dimensional (3D) map reconstruction using an Unmanned Aerial Vehicle (UAV). Due to the need for precise mapping to provide Line-of-Sight (LoS) THz communication services, our approach leverages the UAV's trajectory to initiate the reconstruction and updating of the 3D environment in real-time. The UAV starts without any prior knowledge of the target area, establishing THz communications with users scattered among 3D obstacles. A comprehensive system model is developed, incorporating realistic antenna patterns, UAV oscillations, and received signal power modeling for accurate analysis. We establish an adaptive methodology for 3D environment modeling, dynamically constructing and refining a grid-based obstacle map. A dynamic algorithm for real-time 3D map reconstruction is implemented, utilizing received signal strengths to update the environmental model. Detailed simulations validate the effectiveness of our proposed methods, demonstrating significant improvements in computational efficiency and real-time decision-making in UAV-assisted communication networks. Our results highlight the potential of this joint approach in enhancing operational efficiency and communication reliability under varying environmental conditions.
KW - 3D map reconstruction
KW - THz communication
KW - UAV networks
KW - cloud-based aggregation
KW - obstacle matrix estimation
UR - https://www.scopus.com/pages/publications/85213053492
U2 - 10.1109/VTC2024-Fall63153.2024.10757700
DO - 10.1109/VTC2024-Fall63153.2024.10757700
M3 - Conference contribution
SN - 979-8-3315-1779-3
T3 - IEEE Vehicular Technology Conference
SP - 1
EP - 6
BT - 2024 IEEE 100th Vehicular Technology Conference (VTC2024-Fall)
PB - IEEE
T2 - 100th IEEE Vehicular Technology Conference, VTC 2024-Fall
Y2 - 7 October 2024 through 10 October 2024
ER -