电讯技术2023，Vol.63Issue(12)：1855-1861,7.DOI:10.20079/j.issn.1001-893x.230401001
基于强化学习的无人机电磁干扰感知与抗干扰传输方法
An Electromagnetic Jamming Sensing and Anti-jamming Transmission Method of UAV Based on Reinforcement Learning
摘要
Abstract
The dependence on wireless channel and the openness of wireless channel make unmanned aerial vehicle(UAV)vulnerable to malicious electromagnetic jammings.To combat channel-following jamming from jammers,a reinforcement learning-based anti-jamming strategy is proposed based on the perception of jamming spectrum information.The power control and channel access strategy of UAV is modeled as Markov Decision Process(MDP),and the anti-jamming strategy of the communication system is intelligently optimized by Reinforcement Learning Algorithm.An anti-jamming algorithm based on Win or Learn Fast Policy Hill-climbing(WoLF-PHC)algorithm is proposed.The simulation results prove that the proposed algorithm can reduce the user's Interference-to-Signal Ratio(ISR)less than 0.1,and increase the user's achievable rate by 14%on the basis of the initial value.Compared with Q-learning Algorithm and PHC Algorithm,it has better anti-interference transmission performance.关键词
无人机(UAV)/抗干扰/电磁干扰感知/强化学习Key words
unmanned aerial vehicle(UAV)/anti-jamming/electromagnetic jamming sensing/reinforcement learning分类
信息技术与安全科学引用本文复制引用
李博扬,刘洋,万诺天,许魁,夏晓晨,张月月,张咪..基于强化学习的无人机电磁干扰感知与抗干扰传输方法[J].电讯技术,2023,63(12):1855-1861,7.基金项目
国家自然科学基金资助项目(62071485,62271503,62001513) （62071485,62271503,62001513）
江苏省自然科学基金项目(BK20201334,BK20201334,BK20200579,BK20231485) （BK20201334,BK20201334,BK20200579,BK20231485）
