Large language model-enhanced deep reinforcement learning for secure data collection in low-altitude economy networking

Authors/Creators

• Lingyi Cai
• Ruichen Zhang
• Jiacheng Wang
• Yu Zhang
• Miaoran Peng
• Tao Jiang
• Dusit Niyato
• Wei Ni, Edith Cowan UniversityFollow
• Abbas Jamalipour
• Dong In Kim

Author Identifier (ORCID)

Wei Ni: https://orcid.org/0000-0002-4933-594X

Abstract

Low-altitude economy networking (LAENet) aims to deploy various aerial vehicles to support diverse services, where data collection from edge devices via unmanned aerial vehicles (UAVs) is a critical task. The key challenge lies in jointly optimizing energy consumption and data freshness in spectrum-constrained and eavesdropping-prone low-altitude environments during the data collection process. Although deep reinforcement learning (DRL) has become a viable solution for UAV-assisted data collection, the RL agent still has limited ability to obtain and utilize informative feedback from complex low-altitude environments. In this paper, we propose a large language model (LLM)-enhanced DRL framework for secure data collection in the LAENet, where we leverage an LLM to process environmental feedback for the RL agent. Specifically, we employ the LLM as (i) a state processor to transform basic environmental observations into task-aligned representations, (ii) a reward designer to generate enriched reward signals that guide the agent's actions toward the optimization objective, and (iii) a simulator to construct a virtual LAENet environment for evaluating enhanced state-reward pairs before policy training. Theoretical analysis and numerical results demonstrate that the proposed LLM-enhanced DRL framework achieves faster convergence, improved training stability, and superior performance compared with state-of-the-art baselines.

Keywords

Deep reinforcement learning, large language model, LLM-enhanced DRL, low-altitude economy networking, UAV-assisted data collection

Document Type

Journal Article

Date of Publication

1-1-2026

Publication Title

IEEE Transactions on Mobile Computing

Publisher

IEEE

School

School of Engineering

Comments

Cai, L., Zhang, R., Wang, J., Zhang, Y., Peng, M., Jiang, T., Niyato, D., Ni, W., Jamalipour, A., & Kim, D. I. (2026). Large language model-enhanced deep reinforcement learning for secure data collection in low-altitude economy networking. IEEE Transactions on Mobile Computing. Advance online publication. https://doi.org/10.1109/TMC.2026.3665241

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