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

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arxiv 2504.21583 v1 pith:7AP6MJKY submitted 2025-04-30 cs.NI

classification cs.NI
keywords networksairspacelow-altitudetechnologiesmanagementaerialaircraftapplications
verification ladder T0 review T1 audit T2 compute T3 formal
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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. 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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Cited by 5 Pith papers

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  3. Efficient Onboard Vision-Language Inference in UAV-Enabled Low-Altitude Economy Networks via LLM-Enhanced Optimization

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    A hierarchical ARPO+LLaRA framework that jointly sets image resolution, transmit power, and UAV trajectory reduces simulated latency for onboard VLM inference in low-altitude economy networks.

  4. Curriculum-Guided Heterogeneous Multi-Agent Intelligence for Multi-UAV Cooperative ISAC

    eess.SP 2026-05 unverdicted novelty 3.0 of 10

    Curriculum-based heterogeneous-agent PPO algorithm yields over 30% better sensing performance than baselines in simulated multi-UAV ISAC tasks.

  5. Low-Altitude Wireless Networks: A Comprehensive Survey

    eess.SP 2025-09 unverdicted novelty 2.0 of 10

    A comprehensive survey on low-altitude wireless network (LAWN) systems covering fundamentals, evolution of designs, performance metrics, privacy and security concerns, and airspace structuring for practical deployment.

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