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3TO: THz-Enabled Throughput and Trajectory Optimization of UAVs in 6G Networks by Proximal Policy Optimization Deep Reinforcement Learning
Open accessAbstract
Next-generation networks need to meet ubiquitous and high data-rate demand. Therefore, this paper considers the throughput and trajectory optimization of terahertz (THz)-enabled unmanned aerial vehicles (UAVs) in the sixth-generation (6G) communication networks. In the considered scenario, multiple UAVs must provide on-demand terabits per second (TB/s) services to an urban area along with existing terrestrial networks. However, THz-empowered UAVs pose some new constraints, e.g., dynamic THz-channel conditions for ground users (GUs) association and UAV trajectory optimization to fulfill GU’s throughput demands. Thus, a framework is proposed to address these challenges, where a joint UAVs-GUs association, transmit power, and the trajectory optimization problem is studied. The formulated problem is mixed-integer non-linear programming (MINLP), which is NP-hard to solve. Consequently, an iterative algorithm is proposed to solve three sub-problems iteratively, i.e., UAVs-GUs association, transmit power, and trajectory optimization. Simulation results demonstrate that the proposed algorithm increased the throughput by up to 10%, 68.9%, and 69.1% respectively compared to baseline algorithms.
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From From Google Gemini to OpenAI Q* (Q-Star): A Survey on Reshaping the Generative Artificial Intelligence (AI) Research Landscape (2025) · cites this paper as [212]
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Metadata
- Authors
- Hassan, S. S., Min Park, Y., Tun, Y. K., Saad, W., Han, Z., & Hong, C. S.
- Affiliations
- Kyung Hee University (KR)
- Kyung Hee University,Department of Computer Science and Engineering,Yongin,Republic of Korea,17104
- Virginia Tech (US)
- University of Houston (US)
- Venue
- ICC 2022 - IEEE International Conference on Communications
- Publisher
- IEEE
- Published
- 2022-05-16
- Pages
- 5712-5718
- ISSN
- 1550-3607 (ISSN-L)
- OpenAlex
- W4290996464
- Cited by
- 34
- References
- 22
- Citations by year
- 2026: 4 · 2025: 13 · 2024: 6 · 2023: 9 · 2022: 2
- FWCI
- 13.13
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- International Conference on Communications (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- VBN Forskningsportal (Aalborg Universitet) (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Research Foundation
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › UAV Applications and Optimization
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Wireless Communication Technologies
- Physical Sciences › Engineering › Aerospace Engineering › Satellite Communication Systems
- Keywords
- terahertz communication, unmanned aerial vehicles, 6G, UAV trajectory optimization, throughput maximization, user association, transmit power allocation, deep reinforcement learning, proximal policy optimization, mixed-integer nonlinear programming, urban wireless networks
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