Toward Realization of Low-Altitude Economy Networks: Core Architecture, Integrated Technologies, and Future Directions

The rise of the low-altitude economy (LAE) is propelling urban development and emerging industries by integrating advanced technologies to enhance efficiency, safety, and sustainability in low-altitude operations. The widespread adoption of unmanned aerial vehicles (UAVs) and electric vertical takeoff and landing (eVTOL) aircraft plays a crucial role in enabling key applications within LAE, such as urban logistics, emergency rescue, and aerial mobility. However, unlike traditional UAV networks, LAE networks encounter increased airspace management demands due to dense flying nodes and potential interference with ground communication systems. In addition, there are heightened and extended security risks in real-time operations, particularly the vulnerability of low-altitude aircraft to cyberattacks from ground-based threats. To address these, this paper first explores related standards and core architecture that support the development of LAE networks. Subsequently, we highlight the integration of technologies such as communication, sensing, computing, positioning, navigation, surveillance, flight control, and airspace management. We also analyze how generative artificial intelligence (GAI) contributes to this integration by enabling intelligent adaptation, uncertainty modeling, and real-time optimization. This synergy of multi-technology drives the advancement of real-world LAE applications, particularly in improving operational efficiency, optimizing airspace usage, and ensuring safety. Finally, we outline future research directions for LAE networks, such as intelligent and adaptive optimization, security and privacy protection, sustainable energy and power management, quantum-driven coordination, generative governance, and three-dimensional (3D) airspace coverage, which collectively underscore the potential of collaborative technologies to advance LAE networks.

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Publication Details

Journal
IEEE Transactions on Cognitive Communications and Networking
Published
2025-08-20
DOI
https://doi.org/10.1109/tccn.2025.3601015
Citations
48
Primary Topic
Mobile Agent-Based Network Management
Type
article
Field-Weighted Citation Impact
71.38

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article

Toward Realization of Low-Altitude Economy Networks: Core Architecture, Integrated Technologies, and Future Directions

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48 citations
IEEE Transactions on Cognitive Communications and Networking
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71.38
article

Toward Realization of Low-Altitude Economy Networks: Core Architecture, Integrated Technologies, and Future Directions

Changyuan Zhao, Dong In Kim, Minghao Yin, Yixian Wang, Zemin Sun, Geng Sun, Shuang Liang, Dusit Niyato, Pengfei Wang, Jiahui Li, Wu Jing, Sumei Sun, Jiacheng Wang
article en
48 citations

Abstract

The rise of the low-altitude economy (LAE) is propelling urban development and emerging industries by integrating advanced technologies to enhance efficiency, safety, and sustainability in low-altitude operations. The widespread adoption of unmanned aerial vehicles (UAVs) and electric vertical takeoff and landing (eVTOL) aircraft plays a crucial role in enabling key applications within LAE, such as urban logistics, emergency rescue, and aerial mobility. However, unlike traditional UAV networks, LAE networks encounter increased airspace management demands due to dense flying nodes and potential interference with ground communication systems. In addition, there are heightened and extended security risks in real-time operations, particularly the vulnerability of low-altitude aircraft to cyberattacks from ground-based threats. To address these, this paper first explores related standards and core architecture that support the development of LAE networks. Subsequently, we highlight the integration of technologies such as communication, sensing, computing, positioning, navigation, surveillance, flight control, and airspace management. We also analyze how generative artificial intelligence (GAI) contributes to this integration by enabling intelligent adaptation, uncertainty modeling, and real-time optimization. This synergy of multi-technology drives the advancement of real-world LAE applications, particularly in improving operational efficiency, optimizing airspace usage, and ensuring safety. Finally, we outline future research directions for LAE networks, such as intelligent and adaptive optimization, security and privacy protection, sustainable energy and power management, quantum-driven coordination, generative governance, and three-dimensional (3D) airspace coverage, which collectively underscore the potential of collaborative technologies to advance LAE networks.

IEEE Transactions on Cognitive Communications and NetworkingVol. 11(5)
Agency for Science, Technology and Research (SG), Nanyang Technological University (SG), Northeast Normal University (CN), Jilin University (CN), Dalian University of Technology (CN), Institute for Infocomm Research (SG), Jilin Province Science and Technology Department (CN), Sungkyunkwan University (KR)
National Natural Science Foundation of China
Industry, innovation and infrastructure
Openalex Percentile: Top 0%
Mobile Agent-Based Network Management
71.38
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