[2] [2] ZOU Yulong,ZHU Jia,WANG Xianbin,et al. A survey on wireless security: technical challenges,recent advances,and future trends[J]. Proceedings of the IEEE, 2016,104(9):1727-1765. doi:10.1109/JPROC.2016.2558521.

[3] [3] LI Haitao, LUO Jiawei, LIU Changjun. Selfish bandit-based cognitive anti-jamming strategy for aeronautic swarm network in presence of multiple jammer[J]. IEEE Access, 2019(7):30234-30243. doi:10.1109/ACCESS.2019.2896709.

[5] [5] JIAO Jiyu, SUN Xuehong, FANG Liang, et al. An overview of wireless communication technology using deep learning[J]. China Communications, 2021,18(12):1-36. doi:10.23919/JCC.2021.12.001.

[6] [6] JIANG Kun, SU Dan, ZHENG Yanfu. Intelligent acquisition model of traffic congestion information in the vehicle networking environment based on multi-sensor fusion[J]. International Journal of Vehicle Information and Communication Systems, 2019, 4(2):155-169. doi:10.1504/IJVICS.2019.101512.

[7] [7] GALANOPOULOS A, FOUKALAS F, TSIFTSIS T A. Efficient coexistence of LTE with WiFi in the licensed and unlicensed spectrum aggregation[J]. IEEE Transactions on Cognitive Communications and Networking, 2016, 2(2): 129-140. doi: 10.1109/TCCN.2016.2594780.

[9] [9] HANAWAL M K, ABDEL-RAHMAN M J, KRUNZ M. Joint adaptation of frequency hopping and transmission rate for anti-jamming wireless systems[J]. IEEE Transactions on Mobile Computing, 2016, 15(9): 2247-2259. doi: 10.1109/TMC.2015.2492556.

[10] [10] WANG Jingjing, LIU Meng, ZHANG Yi. Research on intelligent anti-jamming communication with cognitive radio[J]. EAI Endorsed Transactions on Cognitive Communications, 2018,4(14):155074. doi:10.4108/eai.11-5-2018.155074.

[11] [11] ZHAO Lingli. Design of intelligent water-saving irrigation system based on internet of things[J]. Wireless Engineering and Technology, 2022,13(3):33-40. doi:10.4236/wet.2022.133003.

[13] [13] PIRAYESH H,ZENG H C. Jamming attacks and anti-jamming strategies in wireless networks: a comprehensive survey[J]. IEEE Communications Surveys & Tutorials, 2022,24(2):767-809. doi:10.1109/COMST.2022.3159185.

[14] [14] JIAN Yang,LI Yang. Research on intelligent cognitive function enhancement of intelligent robot based on ant colony algorithm[J]. Cognitive Systems Research, 2019(56):203-212. doi:10.1016/j.cogsys.2018.12.014.

[15] [15] MNIH V,KAVUKCUOGLU K,SILVER D,et al. Human-level control through deep reinforcement learning[J]. Nature, 2015(518): 529-533. doi:10.1038/nature14236.

[16] [16] NOH S. Decision-making framework for autonomous driving at road intersections: safeguarding against collision, overly conservative behavior, and violation vehicles[J]. IEEE Transactions on Industrial Electronics, 2019, 66(4): 3275-3286. doi: 10.1109/TIE.2018.2840530.

[17] [17] XU Jianliang, LOU Huaxun, ZHANG Weifeng, et al. An intelligent anti-jamming scheme for cognitive radio based on deep reinforcement learning[J]. IEEE Access, 2020(8):202563-202572. doi:10.1109/ACCESS.2020.3036027.

[18] [18] BIN ISSA R,DAS M,RAHMAN M S,et al. Double deep Q-learning and faster R-CNN-based autonomous vehicle navigation and obstacle avoidance in dynamic environment[J]. Sensors, 2021,21(4):1468. doi:10.3390/s21041468.