信号处理2025，Vol.41Issue(7)：1143-1152,10.DOI:10.12466/xhcl.2025.07.001
面向通信感知一体化的无人机集群上行链路物理层安全传输
Physical Layer Security for UAV Swarm Uplink Transmission with Integrated Sensing and Communication
摘要
Abstract
As a key enabling technology for sixth-generation(6G)communication networks,integrated sensing and communication(ISAC)facilitates both wireless communication and environmental sensing by sharing hardware archi-tectures and signal processing mechanisms.This integration enhances spectrum efficiency while reducing hardware costs.Concurrently,unmanned aerial vehicle(UAV),functioning as intelligent nodes in three-dimensional space,have gained widespread application in many fields,such as military reconnaissance,logistics delivery,and disaster re-sponse,owing to their flexibility,wide coverage,and cost-effectiveness.Investigating ISAC networks integrated with UAVs is essential for enhancing spectrum efficiency and optimizing the utilization of low-altitude resources.However,the broadcast nature of wireless communication presents significant challenges to the secure transmission of sensitive in-formation in ISAC networks.This underscores the need to enhance information security through physical layer security techniques.This study focuses on the physical layer secure transmission in a UAV swarm uplink scenario,wherein a ground ISAC base station transmits confidential information to the UAV swarm while sensing multiple ground targets.Multiple eavesdropping UAV positioned near the UAV swarm attempt to intercept the confidential information.To en-hance the physical layer security performance of the ground ISAC base station tasks,a joint optimization problem is for-mulated involving the transmit beamforming strategy of the ISAC base station and the trajectory planning of the UAV swarm.A deep reinforcement learning(DRL)based algorithm is proposed to solve this optimization problem.First,a sum average secrecy rate maximization problem is formulated under sensing performance constraints and subsequently modeled as a Markov decision process(MDP).The security performance of the ISAC network is then improved through joint optimization of the decision variables via carefully designed action and policy networks.Simulation results demon-strate that the proposed method enhances the average secrecy rate by 185.3%compared to a benchmark algorithm,thereby validating its effectiveness in both trajectory planning and beamforming design.关键词
UAV集群/通信感知一体化/物理层安全/深度强化学习/波束形成Key words
unmanned aerial vehicle(UAV)swarm/integrated sensing and communication(ISAC)/physical layer security/deep reinforcement learning(DRL)/beamforming分类
信息技术与安全科学引用本文复制引用
东润泽,王布宏,张杰勇,翁江,方声忠..面向通信感知一体化的无人机集群上行链路物理层安全传输[J].信号处理,2025,41(7):1143-1152,10.基金项目
国家自然科学基金(62301600,62101560)The National Natural Science Foundation of China(62301600,62101560) （62301600,62101560）
