电子学报2026，Vol.54Issue(3)：1252-1262,11.DOI:10.12263/DZXB.20250620
面向大语言模型协作感知的海域通信抗干扰
Anti-Jamming Maritime Communications for LLM-Assisted Collaborative Perception
摘要
Abstract
Harsh maritime wireless channels and jamming attacks increase the transmission difficulty of sensing data and feedback information,thereby degrading collaborative perception performance.To support large language model(LLM)-assisted collaborative perception and object detection,maritime communications must provide highly reliable trans-mission for multi-modal data such as text,images,videos and point clouds to meet diverse quality-of-service requirements.In this paper,we propose an anti-jamming maritime communications scheme for LLM-assisted collaborative perception.Be-sides the data size,channel gain,and historical performance,the communication environment extracted by LLM based on received multi-modal data and prompt,as well as jamming features obtained via spectrum sensing,are further used to opti-mize the transmit power,channel and LLM selection for transmitting the multi-modal data to support collaborative percep-tion against jamming and interference under harsh channel conditions.A feedback recovery mechanism is designed to ad-dress delayed feedback or loss caused by harsh maritime channels and improve the reliability of multi-modal data transmis-sion.The interaction between maritime terminals and the jammer is formulated as the maritime anti-jamming game and the upper bound in terms of communication and perception performance is provided based on the Nash equilibrium to show the impact of the number of modalities and channel states.Simulation results based on the WaterScenes dataset and LLMs such as LLaVA show the performance gain of our proposed scheme with 13.6%higher perception accuracy,66.2%lower com-munication energy consumption and 21.7%less latency over benchmarks against the Q-learning-based smart jammer.关键词
海域通信/多模态/协作感知/大语言模型/抗干扰/智能通信Key words
maritime communications/multi-modal/collaborative perception/large language model/anti-jamming/intelligent communications分类
信息技术与安全科学引用本文复制引用
刘欢欢,肖亮,林蔚祺,张朋丽,陈灏宇,陈宏毅,汤中卫..面向大语言模型协作感知的海域通信抗干扰[J].电子学报,2026,54(3):1252-1262,11.基金项目
国家自然科学基金(No.U25A20388) （No.U25A20388）
中央高校基本科研业务费专项资金资助项目(No.20720250036) （No.20720250036）
国家重点研发计划(No.2023YFB3107603) National Natural Science Foundation of China(No.U25A20388) （No.2023YFB3107603）
Fundamental Research Funds for the Central Universities(No.20720250036) （No.20720250036）
National Key Research and Development Program of China(No.2023YFB3107603) （No.2023YFB3107603）
