福建电脑2024，Vol.40Issue(5)：27-32,6.DOI:10.16707/j.cnki.fjpc.2024.05.005
DRL下UAV辅助认知无线电网络资源优化研究
Resource Optimization in UAV-Assisted Cognitive Ratio Network Under DRL
郑子滨1
作者信息
- 1. 福州大学电气工程与自动化学院 福州 350108
- 折叠
摘要
Abstract
Cognitive radio and energy harvesting technologies provide ideas for solving the problems of low spectrum utilization and battery limitations.To address the issue of information leakage caused by security threats from eavesdroppers,this paper studies the application of drone collaborative interference to enhance the physical layer security of multiple users,in order to maximize security rate.In the energy harvesting cognitive radio system assisted by UAV in the underlying mode,a multi-agent proximal strategy optimization algorithm is adopted,combined with a long short-term memory network to enhance the learning ability of sequence sample data and improve the training efficiency and effectiveness of the algorithm.The simulation results have verified the effectiveness and scalability of the proposed method.关键词
认知无线电/能量采集/物理层安全/无人机/深度强化学习Key words
Cognitive Radio/Energy Harvesting/Physical Layer Security/Uav/Deep Reinforcement Learning分类
信息技术与安全科学引用本文复制引用
郑子滨..DRL下UAV辅助认知无线电网络资源优化研究[J].福建电脑,2024,40(5):27-32,6.
