Unmanned aerial vehicle emergency communication spectrum scheduling method and system based on dynamic entropy optimization

Through the dynamic entropy optimization of the UAV emergency communication spectrum scheduling method, the DSA and ME-MAAC algorithms are used to optimize spectrum perception and aggregation, which solves the problems of scarce spectrum resources and multi-user competition in disaster relief, and achieves efficient and reliable spectrum utilization and communication guarantee.

CN120769244APending Publication Date: 2025-10-10SHANDONG UNIV
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Patent Information

Application Number
CN202511062534.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-07-31
Publication Date
2025-10-10

AI Technical Summary

Technical Problem

In disaster relief scenarios, drone emergency communication networks face the problems of scarce spectrum resources, limited energy, and dynamic competition among multiple users, resulting in inefficient spectrum utilization and poor communication reliability.

Method used

A spectrum scheduling method for UAV emergency communications based on dynamic entropy optimization is adopted. Through an intelligent distributed spectrum management mechanism, DSA and ME-MAAC algorithms are used for spectrum perception and aggregation. The spectrum access strategy is optimized in combination with a deep reinforcement learning model to ensure the priority of primary users and efficient access of secondary users.

Benefits of technology

It significantly improves spectrum utilization efficiency, reduces conflict rates, ensures high quality and reliability of rescue communications, meets the differentiated bandwidth requirements of multiple users, and adapts to dynamic spectrum environments.

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Abstract

The invention relates to an unmanned aerial vehicle emergency communication spectrum scheduling method and system based on dynamic entropy optimization, and the method comprises the steps: 1, constructing an emergency communication system, and calculating the gain of a received signal; 2, constructing a spectrum sensing and user access model; step 3, evaluating the channel quality in the emergency communication system; 4, establishing a state, an action and a reward of deep reinforcement learning according to spectrum sensing, a user access model and channel quality evaluation; 5, constructing a deep reinforcement learning model, and performing training to obtain a trained deep reinforcement learning model; and step 6, obtaining an optimal strategy of unmanned aerial vehicle emergency communication spectrum scheduling in a spectrum environment by using the trained deep reinforcement learning model, and realizing multi-user aggregation spectrum access. According to the invention, through intelligent distributed spectrum management, the problems of limited spectrum resources and energy, multi-user dynamic competition and the like in a disaster rescue scene are solved, and the spectrum utilization efficiency and the communication reliability are remarkably improved.
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