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Large Language Model Agents for Radio Map Generation and Wireless Network Planning

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  • معلومة اضافية
    • بيانات النشر:
      IEEE
    • الموضوع:
      2025
    • Collection:
      University of Hong Kong: HKU Scholars Hub
    • نبذة مختصرة :
      Using commercial software for radio map generation and wireless network planning often require complex manual operations, posing significant challenges in terms of scalability, adaptability, and user-friendliness, due to heavy manual operations. To address these issues, we propose an automated solution that employs large language model (LLM) agents. These agents are designed to autonomously generate radio maps and facilitate wireless network planning for specified areas, thereby minimizing the necessity for extensive manual intervention. To validate the effectiveness of our proposed solution, we develop a software platform that integrates LLM agents. Experimental results demonstrate that a large amount manual operations can be saved via the proposed LLM agent, and the automated solutions can achieve an enhanced coverage and signal-to-interference-noise ratio (SINR), especially in urban environments.
    • Relation:
      IEEE Networking Letters; IEEE Networking Letters, 2025; https://hub.hku.hk/handle/10722/361994
    • الرقم المعرف:
      10.1109/LNET.2025.3539829
    • الدخول الالكتروني :
      https://hub.hku.hk/handle/10722/361994
      https://doi.org/10.1109/LNET.2025.3539829
    • Rights:
      This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
    • الرقم المعرف:
      edsbas.E6F469DF